In [9]:
import pandas as pd

In [10]:
df = pd.read_excel("richpeople.xlsx")
print(df)


      year                          name  rank           citizenship  \
0     2001           A Jerrold Perenchio   151         United States   
1     2014          A. Jerrold Perenchio   663         United States   
2     2001   Abdul Al Rahman  Al Jeraisy   336          Saudi Arabia   
3     2001         Abdul Aziz Al Ghurair   251  United Arab Emirates   
4     1996        Abdul Aziz Al-Sulaiman   404          Saudi Arabia   
5     2014            Abdulla Al Futtaim   687  United Arab Emirates   
6     2014  Abdulla bin Ahmad Al Ghurair   305  United Arab Emirates   
7     2001             Abdullah Al Rajhi   222          Saudi Arabia   
8     2014             Abdullah Al Rajhi   731          Saudi Arabia   
9     2014              Abdulsamad Rabiu  1372               Nigeria   
10    1996               Abigail Johnson   145         United States   
11    2001               Abigail Johnson    30         United States   
12    2014               Abigail Johnson    50         United States   
13    1996       Abilio dos Santos Diniz   322                Brazil   
14    2001       Abilio dos Santos Diniz   312                Brazil   
15    2014       Abilio dos Santos Diniz   609                Brazil   
16    2001             Achille Maramotti   222                 Italy   
17    2014                 Achmad Hamami  1092             Indonesia   
18    2014                    Adi Godrej   446                 India   
19    1996                 Adolf Merckle   388               Germany   
20    2001                 Adolf Merckle   222               Germany   
21    1996         Adrian and John Swire   162             Hong Kong   
22    2001                  Adrian Swire   222        United Kingdom   
23    2014      Aerin Lauder Zinterhofer  1465         United States   
24    1996               Ahmed Ali Kanoo   383               Bahrain   
25    2014                   Ahmet Calik  1465                Turkey   
26    2014             Ahmet Nazif Zorlu  1372                Turkey   
27    2014                  Ahsen Ozokur  1143                Turkey   
28    2014                Airat Shaimiev  1465                Russia   
29    2014                    Ajay Kalsi   973                 India   
...    ...                           ...   ...                   ...   
2584  2014                   Yuri Milner   988                Russia   
2585  2014                  Yuriy Kosiuk  1154               Ukraine   
2586  2014                Yusaku Maezawa  1356                 Japan   
2587  2014                  Yusuf Hamied  1465                 India   
2588  2014                  Yvonne Bauer   446               Germany   
2589  2014                    Zadik Bino  1540                Israel   
2590  2014                  Zarakh Iliev   430                Russia   
2591  2014                 Zdenek Bakala  1565        Czech Republic   
2592  2014             Zelimkhan Mutsoev  1284                Russia   
2593  2014               Zhang Changhong  1203                 China   
2594  2014                 Zhang Guiping  1465                 China   
2595  2014                 Zhang Hongwei  1046                 China   
2596  2014                 Zhang Jindong   408                 China   
2597  2014                      Zhang Li   828                 China   
2598  2014                 Zhang Shiping   430                 China   
2599  2014                     Zhang Xin   408                 China   
2600  2014                 Zhang Zhidong   305                 China   
2601  2014                 Zhang Zhirong   988             Hong Kong   
2602  2014               Zhang Zhongneng  1372                 China   
2603  2014              Zhong Sheng Jian  1372             Singapore   
2604  2014                Zhou Chengjian  1092                 China   
2605  2014                   Zhou Hongyi   828                 China   
2606  2014                  Zhu Gongshan   828                 China   
2607  2014                   Zhu Wenchen  1565                 China   
2608  2014                 Zhu Xingliang   988                 China   
2609  2014                     Zhu Yicai  1154                 China   
2610  2014                 Ziyad Manasir   609                Russia   
2611  2014            Ziyaudin Magomedov  1372                Russia   
2612  2014                  Zong Qinghou    94                 China   
2613  2014            Zygmunt Solorz-Zak   446                Poland   

     countrycode  networthusbillion   selfmade              typeofwealth  \
0            USA                3.0  self-made                 executive   
1            USA                2.6  self-made                 executive   
2            SAU                1.5  self-made       founder non-finance   
3            ARE                1.9  inherited                 inherited   
4            SAU                1.0  self-made         self-made finance   
5            ARE                2.5  inherited                 inherited   
6            ARE                4.8  inherited                 inherited   
7            SAU                2.1  self-made         self-made finance   
8            SAU                2.4  self-made         self-made finance   
9            NGA                1.2  self-made       founder non-finance   
10           USA                2.5  inherited                 inherited   
11           USA                9.1  inherited                 inherited   
12           USA               17.3  inherited                 inherited   
13           BRA                1.2  inherited                 inherited   
14           BRA                1.6  inherited                 inherited   
15           BRA                2.8  inherited                 inherited   
16           ITA                2.1  self-made       founder non-finance   
17           IDN                1.6  self-made       founder non-finance   
18           IND                3.5  inherited                 inherited   
19           DEU                1.0  inherited                 inherited   
20           DEU                2.1  inherited                 inherited   
21           HKG                2.2  inherited                 inherited   
22           GBR                2.1  inherited                 inherited   
23           USA                1.1  inherited                 inherited   
24           BHR                1.0  inherited                 inherited   
25           TUR                1.1  self-made  privatized and resources   
26           TUR                1.2  self-made         self-made finance   
27           TUR                1.6  inherited                 inherited   
28           RUS                1.1  self-made  privatized and resources   
29           IND                1.9  self-made  privatized and resources   
...          ...                ...        ...                       ...   
2584         RUS                1.8  self-made       founder non-finance   
2585         UKR                1.5  self-made       founder non-finance   
2586         JPN                1.3  self-made       founder non-finance   
2587         IND                1.1  inherited                 inherited   
2588         DEU                3.5  inherited                 inherited   
2589         ISR                1.1  self-made         self-made finance   
2590         RUS                3.6  self-made         self-made finance   
2591         CZE                1.0  self-made  privatized and resources   
2592         RUS                1.3  self-made                 executive   
2593         CHN                1.5  self-made         self-made finance   
2594         CHN                1.1  self-made         self-made finance   
2595         CHN                1.7  self-made         self-made finance   
2596         CHN                3.7  self-made       founder non-finance   
2597         CHN                2.1  self-made         self-made finance   
2598         CHN                3.6  self-made  privatized and resources   
2599         CHN                3.7  self-made         self-made finance   
2600         CHN                4.8  self-made       founder non-finance   
2601         HKG                1.8  self-made                 executive   
2602         CHN                1.2  self-made  privatized and resources   
2603         SGP                1.2  self-made         self-made finance   
2604         CHN                1.6  self-made       founder non-finance   
2605         CHN                2.1  self-made       founder non-finance   
2606         CHN                2.1  self-made  privatized and resources   
2607         CHN                1.0  self-made                 executive   
2608         CHN                1.8  self-made                 executive   
2609         CHN                1.5  self-made         self-made finance   
2610         RUS                2.8  self-made  privatized and resources   
2611         RUS                1.2  self-made  privatized and resources   
2612         CHN               11.6  self-made       founder non-finance   
2613         POL                3.5  self-made       founder non-finance   

      gender   age   ...       relationshiptocompany foundingdate  \
0       male  70.0   ...     former chairman and CEO       1955.0   
1       male  83.0   ...     former chairman and CEO       1955.0   
2       male   NaN   ...                     founder       1956.0   
3       male  47.0   ...                    relation       1960.0   
4       male   0.0   ...                     founder       1968.0   
5       male   NaN   ...                    relation       1930.0   
6       male   NaN   ...                    relation       1960.0   
7       male   NaN   ...                     founder       1957.0   
8       male   NaN   ...                     founder       1957.0   
9       male  54.0   ...                     founder       1988.0   
10    female  34.0   ...                    relation       1946.0   
11    female  39.0   ...                    relation       1946.0   
12    female  52.0   ...                    relation       1946.0   
13      male  59.0   ...                    relation       1948.0   
14      male  64.0   ...                    relation       1948.0   
15      male  77.0   ...                    relation       1948.0   
16      male  74.0   ...                     founder       1951.0   
17      male  83.0   ...                     founder       1980.0   
18      male  71.0   ...                    relation       1897.0   
19      male  61.0   ...                    relation       1881.0   
20      male  66.0   ...                    relation       1881.0   
21      male   0.0   ...                    relation       1816.0   
22      male  70.0   ...                    relation       1816.0   
23    female  44.0   ...                    relation       1946.0   
24      male   0.0   ...                    relation       1890.0   
25      male  56.0   ...                    relation       1981.0   
26      male  69.0   ...                     founder       1953.0   
27    female  63.0   ...                    relation       1944.0   
28      male  51.0   ...                       owner       1995.0   
29      male  53.0   ...                     founder       1998.0   
...      ...   ...   ...                         ...          ...   
2584    male  52.0   ...                     founder       1999.0   
2585    male  45.0   ...                     founder       1998.0   
2586    male  38.0   ...                     founder       2004.0   
2587    male  77.0   ...                    relation       1935.0   
2588  female  36.0   ...                    relation       1875.0   
2589    male  70.0   ...                       owner       1922.0   
2590    male  47.0   ...                     founder          NaN   
2591    male  53.0   ...                     founder       1994.0   
2592    male  54.0   ...                       owner       2004.0   
2593    male  55.0   ...                    chairman       2000.0   
2594    male  62.0   ...                    chairman       1990.0   
2595    male  59.0   ...                    chairman       2007.0   
2596    male  50.0   ...           founder/president       1990.0   
2597    male  61.0   ...                    chairman       1994.0   
2598    male  67.0   ...                     founder       1994.0   
2599  female  48.0   ...                     founder       1995.0   
2600    male  42.0   ...                     founder       1998.0   
2601    male  45.0   ...                         CEO       2005.0   
2602    male  50.0   ...                       owner       1993.0   
2603    male  56.0   ...                     founder       1993.0   
2604    male  48.0   ...                     founder       1986.0   
2605    male  43.0   ...                     founder       2005.0   
2606    male  56.0   ...                     founder       2008.0   
2607    male  48.0   ...                    chairman       1999.0   
2608    male  54.0   ...                    investor       1994.0   
2609    male  49.0   ...                     founder       1993.0   
2610    male  48.0   ...                     founder       1992.0   
2611    male  45.0   ...                     founder       2004.0   
2612    male  68.0   ...                     founder       1987.0   
2613    male  57.0   ...                     founder       1992.0   

      gdpcurrentus               sourceofwealth  \
0     1.062180e+13                          NaN   
1              NaN        television, Univision   
2     1.830120e+11                          NaN   
3     1.030000e+11                          NaN   
4     1.577430e+11                          NaN   
5              NaN    auto dealers, investments   
6              NaN                  diversified   
7     1.830120e+11                          NaN   
8              NaN                      banking   
9              NaN         sugar, flour, cement   
10    8.100200e+12                          NaN   
11    1.062180e+13                          NaN   
12             NaN             money management   
13    8.540000e+11                          NaN   
14    5.600000e+11                          NaN   
15             NaN                       retail   
16    1.160000e+12                          NaN   
17             NaN              heavy equipment   
18             NaN               consumer goods   
19    2.500000e+12                          NaN   
20    1.950000e+12                          NaN   
21    1.600000e+11                          NaN   
22    1.530000e+12                          NaN   
23             NaN         inherited, cosmetics   
24    6.100000e+09                          NaN   
25             NaN       energy, media, banking   
26             NaN                  diversified   
27             NaN           food manufacturing   
28             NaN          refinery, chemicals   
29             NaN                  oil and gas   
...            ...                          ...   
2584           NaN                     Facebook   
2585           NaN                  agriculture   
2586           NaN                online retail   
2587           NaN               pharmceuticals   
2588           NaN                        media   
2589           NaN                 banking, oil   
2590           NaN                  real estate   
2591           NaN                         coal   
2592           NaN     fertilizers, real estate   
2593           NaN  finance information service   
2594           NaN                  real estate   
2595           NaN                  diversified   
2596           NaN                       retail   
2597           NaN                  real estate   
2598           NaN                       metals   
2599           NaN                  real estate   
2600           NaN               internet media   
2601           NaN                 shipbuilding   
2602           NaN                     aluminum   
2603           NaN                  real estate   
2604           NaN                       retail   
2605           NaN                     Internet   
2606           NaN        solar panel materials   
2607           NaN              pharmaceuticals   
2608           NaN                 construction   
2609           NaN                  diversified   
2610           NaN                 construction   
2611           NaN                    port, gas   
2612           NaN                    beverages   
2613           NaN              TV broadcasting   

                                                  notes  \
0        represented Marlon Brando and Elizabeth Taylor   
1        represented Marlon Brando and Elizabeth Taylor   
2                                                   NaN   
3                                 inherited from father   
4                                                   NaN   
5          company split between him and cousin in 2000   
6                                 inherited from father   
7                                                   NaN   
8                                                   NaN   
9                                                   NaN   
10                                       3rd generation   
11                                       3rd generation   
12                                       3rd generation   
13    kidnapped for 6 days in 1989, inherited from f...   
14    kidnapped for 6 days in 1989, inherited from f...   
15    kidnapped for 6 days in 1989, inherited from f...   
16                                                  NaN   
17                                                  NaN   
18                                       3rd generation   
19                                       4th generation   
20                                       4th generation   
21                                   fourth generation?   
22                                   fourth generation?   
23                                       3rd generation   
24                                       3rd generation   
25    family involved in textile business from 1930,...   
26                                                  NaN   
27                                inherited from father   
28                                                  NaN   
29                                                  NaN   
...                                                 ...   
2584                                                NaN   
2585                                                NaN   
2586                                                NaN   
2587                              inherited from father   
2588                                     5th generation   
2589                                                NaN   
2590                                                NaN   
2591                                                NaN   
2592                                                NaN   
2593                                                NaN   
2594                                                NaN   
2595                   only private chinese oil company   
2596                                                NaN   
2597                                                NaN   
2598                                                NaN   
2599                                                NaN   
2600                                                NaN   
2601                                                NaN   
2602                                                NaN   
2603                                                NaN   
2604                                                NaN   
2605                          former CEO of Yahoo China   
2606                                                NaN   
2607                                                NaN   
2608             arrested in 2013 on corruption charges   
2609                                                NaN   
2610                            close ties with Gazprom   
2611                                                NaN   
2612                                                NaN   
2613                                                NaN   

                                                 notes2  \
0                                                   NaN   
1                                                   NaN   
2                                                   NaN   
3                                                   NaN   
4                                                   NaN   
5                                                   NaN   
6                                                   NaN   
7                                                   NaN   
8                                                   NaN   
9                                                   NaN   
10                                     no male siblings   
11                                     no male siblings   
12                                     no male siblings   
13                                                  NaN   
14                                                  NaN   
15                                                  NaN   
16                                                  NaN   
17                                                  NaN   
18                                                  NaN   
19                                                  NaN   
20                                                  NaN   
21                                                  NaN   
22                                                  NaN   
23                                                  NaN   
24    With the permission and support of past Bahrai...   
25                                                  NaN   
26                                                  NaN   
27                                          shareholder   
28                                                  NaN   
29                                                  NaN   
...                                                 ...   
2584                                                NaN   
2585                                                NaN   
2586                                                NaN   
2587                                                NaN   
2588  chairman, three sisters have 5% ownership in c...   
2589                                                NaN   
2590                                                NaN   
2591                                                NaN   
2592                                                NaN   
2593                                                NaN   
2594                                                NaN   
2595                                                NaN   
2596                                                NaN   
2597                                                NaN   
2598                                                NaN   
2599                                                NaN   
2600                                                NaN   
2601                                                NaN   
2602                                                NaN   
2603                                                NaN   
2604                                                NaN   
2605                                                NaN   
2606                                                NaN   
2607                                                NaN   
2608                                                NaN   
2609                                                NaN   
2610                                                NaN   
2611                                                NaN   
2612                                                NaN   
2613                                                NaN   

                                                 source  \
0          http://en.wikipedia.org/wiki/Jerry_Perenchio   
1          http://en.wikipedia.org/wiki/Jerry_Perenchio   
2     http://www.jeraisy.com.sa/index.php/pages/rend...   
3                                                   NaN   
4     http://www.arabianbusiness.com/arabian-busines...   
5         http://en.wikipedia.org/wiki/Al-Futtaim_Group   
6         http://en.wikipedia.org/wiki/Al-Ghurair_Group   
7            http://en.wikipedia.org/wiki/Al-Rajhi_Bank   
8            http://en.wikipedia.org/wiki/Al-Rajhi_Bank   
9       http://www.forbes.com/profile/abdulsamad-rabiu/   
10     http://en.wikipedia.org/wiki/Edward_Johnson,_III   
11     http://en.wikipedia.org/wiki/Edward_Johnson,_III   
12     http://en.wikipedia.org/wiki/Edward_Johnson,_III   
13       http://en.wikipedia.org/wiki/Ab%C3%ADlio_Diniz   
14       http://en.wikipedia.org/wiki/Ab%C3%ADlio_Diniz   
15       http://en.wikipedia.org/wiki/Ab%C3%ADlio_Diniz   
16    http://www.independent.co.uk/news/obituaries/a...   
17         http://www.forbes.com/profile/achmad-hamami/   
18           http://en.wikipedia.org/wiki/Godrej_family   
19                                                  NaN   
20                                                  NaN   
21           http://www.swire.com/en/about-us/our-story   
22           http://www.swire.com/en/about-us/our-story   
23             http://en.wikipedia.org/wiki/Jane_Lauder   
24    http://www.gulf-daily-news.com/NewsDetails.asp...   
25    http://en.wikipedia.org/wiki/Ahmet_%C3%87al%C4...   
26     http://www.forbes.com/profile/ahmet-nazif-zorlu/   
27              http://en.wikipedia.org/wiki/%C3%9Clker   
28        http://www.forbes.com/profile/airat-shaimiev/   
29              http://en.wikipedia.org/wiki/Ajay_Kalsi   
...                                                 ...   
2584           http://en.wikipedia.org/wiki/Yuri_Milner   
2585        http://www.forbes.com/profile/yuriy-kosiuk/   
2586        http://en.wikipedia.org/wiki/Yusaku_Maezawa   
2587          http://en.wikipedia.org/wiki/Yusuf_Hamied   
2588        http://www.forbes.com/profile/yvonne-bauer/   
2589            http://en.wikipedia.org/wiki/Zadik_Bino   
2590        http://www.forbes.com/profile/zarakh-iliev/   
2591    http://cs.wikipedia.org/wiki/Zden%C4%9Bk_Bakala   
2592   http://www.forbes.com/profile/zelimkhan-mutsoev/   
2593     http://www.forbes.com/profile/zhang-changhong/   
2594       http://www.forbes.com/profile/zhang-guiping/   
2595  http://www.forbes.com/sites/russellflannery/20...   
2596         http://en.wikipedia.org/wiki/Zhang_Jindong   
2597  http://www.rfchina.com/2010e/display.aspx?cati...   
2598       http://www.forbes.com/profile/zhang-shiping/   
2599  http://en.wikipedia.org/wiki/Zhang_Xin_(busine...   
2600  http://www.forbes.com/sites/russellflannery/20...   
2601       http://www.forbes.com/profile/zhang-zhirong/   
2602     http://www.forbes.com/profile/zhang-zhongneng/   
2603    http://www.forbes.com/profile/zhong-sheng-jian/   
2604        http://en.wikipedia.org/wiki/Zhou_Chengjian   
2605         http://www.forbes.com/profile/zhou-hongyi/   
2606  http://investing.businessweek.com/research/sto...   
2607       http://www.furenpharm.com/aboutus.asp?cid=82   
2608       http://www.forbes.com/profile/zhu-xingliang/   
2609           http://www.forbes.com/profile/zhu-yicai/   
2610       http://www.forbes.com/profile/ziyad-manasir/   
2611         http://www.summagroup.ru/about/history/en/   
2612          http://en.wikipedia.org/wiki/Zong_Qinghou   
2613  http://en.wikipedia.org/wiki/Zygmunt_Solorz-%C...   

                                               source_2  \
0     http://www.forbes.com/profile/a-jerrold-perenc...   
1     http://www.forbes.com/profile/a-jerrold-perenc...   
2                                                   NaN   
3                                                   NaN   
4                                                   NaN   
5     http://www.al-futtaim.ae/content/groupProfile.asp   
6         http://www.alghurair.com/about-us/our-history   
7     http://www.alrajhibank.com.sa/ar/investor-rela...   
8     http://www.alrajhibank.com.sa/ar/investor-rela...   
9     http://www.bloomberg.com/research/stocks/priva...   
10    https://www.fidelity.com/about-fidelity/our-he...   
11    https://www.fidelity.com/about-fidelity/our-he...   
12    https://www.fidelity.com/about-fidelity/our-he...   
13    http://www.forbes.com/profile/abilio-dos-santo...   
14    http://www.forbes.com/profile/abilio-dos-santo...   
15    http://www.forbes.com/profile/abilio-dos-santo...   
16                                                  NaN   
17    http://www.trakindo.co.id/website/pages/compan...   
18                http://www.forbes.com/profile/godrej/   
19                                                  NaN   
20                                                  NaN   
21                                                  NaN   
22                                                  NaN   
23    http://investing.businessweek.com/research/sto...   
24    http://en.wikipedia.org/wiki/Yusuf_Bin_Ahmed_K...   
25    http://en.wikipedia.org/wiki/%C3%87al%C4%B1k_H...   
26      http://www.zorlu.com/EN/ZORLU/zor_kurucumuz.asp   
27        http://www.yildizholding.com.tr/tr/hakkimizda   
28                                   http://en.taif.ru/   
29             http://www.indusgas.com/history.php?p=ab   
...                                                 ...   
2584  Science prize announced by Google and Facebook...   
2585             http://www.mhp.com.ua/en/about/history   
2586                                                NaN   
2587   http://en.wikipedia.org/wiki/Khwaja_Abdul_Hamied   
2588     http://en.wikipedia.org/wiki/Bauer_Media_Group   
2589  http://en.wikipedia.org/wiki/Paz_Oil_Company_Ltd.   
2590  http://www.themoscowtimes.com/news/article/lot...   
2591                                                NaN   
2592                  http://regionsgroup.ru/en/about1/   
2593                       http://www.dzhnews.com/about   
2594                                                NaN   
2595                                                NaN   
2596      http://en.wikipedia.org/wiki/Suning_Appliance   
2597          http://www.forbes.com/profile/zhang-li-1/   
2598          http://www.hongqiaochina.com/en/dsgg.aspx   
2599                                                NaN   
2600  http://www.therichest.com/celebnetworth/celebr...   
2601            http://en.rshi.cn/html/ABOUTUS/History/   
2602                   http://www.hec-al.com/about.html   
2603      http://www.yanlordland.com/en/About_Us5_1.asp   
2604  http://www.cnbc.com/2016/01/18/missing-chinese...   
2605                 http://en.wikipedia.org/wiki/Qihoo   
2606  http://gcl-poly.com.hk/en/about_history.php?ye...   
2607         http://www.forbes.com/profile/zhu-wenchen/   
2608      http://www.goldmantis.com/jtl2013/cn/xxgl.htm   
2609                                                NaN   
2610  http://www.themoscowtimes.com/business/article...   
2611  http://www.forbes.com/profile/ziyaudin-magomedov/   
2612  http://mic.com/articles/39659/zong-qinghou-chi...   
2613  No Mob Bosses in This Legal Strategy The New Y...   

                                               source_3 source_4  
0     COLUMN ONE; A Hollywood Player Who Owns the Ga...      NaN  
1     COLUMN ONE; A Hollywood Player Who Owns the Ga...      NaN  
2                                                   NaN      NaN  
3                                                   NaN      NaN  
4                                                   NaN      NaN  
5                                                   NaN      NaN  
6                                                   NaN      NaN  
7     http://www.alrajhibank.com.sa/ar/about-us/page...      NaN  
8     http://www.alrajhibank.com.sa/ar/about-us/page...      NaN  
9                                                   NaN      NaN  
10                                                  NaN      NaN  
11                                                  NaN      NaN  
12                                                  NaN      NaN  
13                                                  NaN      NaN  
14                                                  NaN      NaN  
15                                                  NaN      NaN  
16                                                  NaN      NaN  
17                                                  NaN      NaN  
18                                                  NaN      NaN  
19                                                  NaN      NaN  
20                                                  NaN      NaN  
21                                                  NaN      NaN  
22                                                  NaN      NaN  
23                                                  NaN      NaN  
24                                                  NaN      NaN  
25         http://www.calik.com/en/corporate/milestones      NaN  
26    http://www.bloomberg.com/bw/stories/2003-07-06...      NaN  
27                                                  NaN      NaN  
28                                                  NaN      NaN  
29                                                  NaN      NaN  
...                                                 ...      ...  
2584                                                NaN      NaN  
2585               http://www.mhp.com.ua/en/about/board      NaN  
2586                                                NaN      NaN  
2587                                                NaN      NaN  
2588                                                NaN      NaN  
2589                                                NaN      NaN  
2590                                                NaN      NaN  
2591                                                NaN      NaN  
2592                                                NaN      NaN  
2593                                                NaN      NaN  
2594                                                NaN      NaN  
2595                                                NaN      NaN  
2596  http://topics.wsj.com/person/Z/jindong-zhang/6799      NaN  
2597                                                NaN      NaN  
2598                                                NaN      NaN  
2599                                                NaN      NaN  
2600                                                NaN      NaN  
2601                                                NaN      NaN  
2602                                                NaN      NaN  
2603                                                NaN      NaN  
2604                                                NaN      NaN  
2605                                                NaN      NaN  
2606                                                NaN      NaN  
2607                                                NaN      NaN  
2608                                                NaN      NaN  
2609                                                NaN      NaN  
2610                                                NaN      NaN  
2611                                                NaN      NaN  
2612                                                NaN      NaN  
2613                                                NaN      NaN  

[2614 rows x 30 columns]

What country are most billionaires from? For the top ones, how many billionaires per billion people?


In [11]:
df['citizenship'].value_counts().head()


Out[11]:
United States    903
Germany          160
China            153
Russia           119
Japan             96
Name: citizenship, dtype: int64

In [ ]:
us_pop = 318.9 #billion (2014)
us_bill = df[df['citizenship'] == 'United States']
print("There are",  us_pop/len(us_bill), "billionaires per billion people in the United States.")

In [15]:
germ_pop = 0.08062 #(2013)
germ_bill = df[df['citizenship'] == 'Germany']
print("There are",  germ_pop/len(germ_bill), "billionaires per billion people in Germany.")


There are 0.000503875 billionaires per billion people in Germany.

In [16]:
china_pop = 1.357 #(2013)
china_bill = df[df['citizenship'] == 'China']
print("There are",  china_pop/len(china_bill), "billionaires per billion people in China.")


There are 0.008869281045751633 billionaires per billion people in China.

In [ ]:
russia_pop = 0.1435 #(2013)
russia_bill = df[df['citizenship'] == 'Russia']
print("There are",  russia_pop/len(russia_bill), "billionaires per billion people in Russia.")


There are 0.0012058823529411764 billionaires per billion people in Russia.

In [7]:
japan_pop = 0.1273 # 2013 
japan_bill = df[df['citizenship'] == 'Japan']
print("There are",  japan_pop/len(japan_bill), "billionaires per billion people in Japan.")


There are 0.0013260416666666666 billionaires per billion people in Japan.

In [8]:
print(df.columns)


Index(['year', 'name', 'rank', 'citizenship', 'countrycode',
       'networthusbillion', 'selfmade', 'typeofwealth', 'gender', 'age',
       'industry', 'IndustryAggregates', 'region', 'north',
       'politicalconnection', 'founder', 'generationofinheritance', 'sector',
       'company', 'companytype', 'relationshiptocompany', 'foundingdate',
       'gdpcurrentus', 'sourceofwealth', 'notes', 'notes2', 'source',
       'source_2', 'source_3', 'source_4'],
      dtype='object')

Who are the top 10 richest billionaires?


In [26]:
recent = df[df['year'] == 2014]
# if it is not recent then there are duplicates for diff years
recent.sort_values('rank').head(10)


Out[26]:
year name rank citizenship countrycode networthusbillion selfmade typeofwealth gender age ... relationshiptocompany foundingdate gdpcurrentus sourceofwealth notes notes2 source source_2 source_3 source_4
284 2014 Bill Gates 1 United States USA 76.0 self-made founder non-finance male 58.0 ... founder 1975.0 NaN Microsoft NaN NaN http://www.forbes.com/profile/bill-gates/ NaN NaN NaN
348 2014 Carlos Slim Helu 2 Mexico MEX 72.0 self-made privatized and resources male 74.0 ... founder 1990.0 NaN telecom NaN NaN http://www.ozy.com/provocateurs/carlos-slims-w... NaN NaN NaN
124 2014 Amancio Ortega 3 Spain ESP 64.0 self-made founder non-finance male 77.0 ... founder 1975.0 NaN retail NaN NaN http://www.forbes.com/profile/amancio-ortega/ NaN NaN NaN
2491 2014 Warren Buffett 4 United States USA 58.2 self-made founder non-finance male 83.0 ... founder 1839.0 NaN Berkshire Hathaway NaN NaN http://www.forbes.com/lists/2009/10/billionair... http://www.forbes.com/companies/berkshire-hath... NaN NaN
1377 2014 Larry Ellison 5 United States USA 48.0 self-made founder non-finance male 69.0 ... founder 1977.0 NaN Oracle NaN NaN http://www.forbes.com/profile/larry-ellison/ http://www.businessinsider.com/how-larry-ellis... NaN NaN
509 2014 David Koch 6 United States USA 40.0 inherited inherited male 73.0 ... relation 1940.0 NaN diversified inherited from father NaN http://www.kochind.com/About_Koch/History_Time... NaN NaN NaN
381 2014 Charles Koch 6 United States USA 40.0 inherited inherited male 78.0 ... relation 1940.0 NaN diversified inherited from father NaN http://www.kochind.com/About_Koch/History_Time... NaN NaN NaN
2185 2014 Sheldon Adelson 8 United States USA 38.0 self-made self-made finance male 80.0 ... founder 1952.0 NaN casinos NaN NaN http://www.forbes.com/profile/sheldon-adelson/ http://lasvegassun.com/news/1996/nov/26/rat-pa... NaN NaN
429 2014 Christy Walton 9 United States USA 36.7 inherited inherited female 59.0 ... relation 1962.0 NaN Wal-Mart widow NaN http://www.forbes.com/profile/christy-walton/ NaN NaN NaN
1128 2014 Jim Walton 10 United States USA 34.7 inherited inherited male 66.0 ... relation 1962.0 NaN Wal-Mart inherited from father NaN http://www.forbes.com/profile/jim-walton/ NaN NaN NaN

10 rows × 30 columns

What's the average wealth of a billionaire? Male? Female?

What's the average wealth of a billionaire? Male? Female


In [11]:
print("The average wealth of a billionaire is", recent['networthusbillion'].mean(), "billion dollars")

male = recent[(recent['gender'] == 'male')]
female = recent[(recent['gender'] == 'female')]


print("The average wealth of a male billionaire is", male['networthusbillion'].mean(), "billion dollars")
print("The average wealth of a female billionaire is", female['networthusbillion'].mean(), "billion dollars")


The average wealth of a billionaire is 3.90465819722 billion dollars
The average wealth of a male billionaire is 3.9027155465 billion dollars
The average wealth of a female billionaire is 3.92055555556 billion dollars

Who is the poorest billionaire?


In [69]:
recent.sort_values('networthusbillion').head(1)


Out[69]:
year name rank citizenship countrycode networthusbillion selfmade typeofwealth gender age ... relationshiptocompany foundingdate gdpcurrentus sourceofwealth notes notes2 source source_2 source_3 source_4
234 2014 B.R. Shetty 1565 India IND 1.0 self-made founder non-finance male 72.0 ... founder 1975.0 NaN healthcare NaN NaN http://en.wikipedia.org/wiki/B._R._Shetty http://www.nmchealth.com/dr-br-shetty/ NaN NaN

1 rows × 30 columns


In [48]:
# Who are the top 10 poorest billionaires?

In [ ]:
# Who are the top 10 poorest billionaires

In [27]:
recent.sort_values('networthusbillion').head(10)


Out[27]:
year name rank citizenship countrycode networthusbillion selfmade typeofwealth gender age ... relationshiptocompany foundingdate gdpcurrentus sourceofwealth notes notes2 source source_2 source_3 source_4
234 2014 B.R. Shetty 1565 India IND 1.0 self-made founder non-finance male 72.0 ... founder 1975.0 NaN healthcare NaN NaN http://en.wikipedia.org/wiki/B._R._Shetty http://www.nmchealth.com/dr-br-shetty/ NaN NaN
2092 2014 Rostam Azizi 1565 Tanzania TZA 1.0 self-made executive male 49.0 ... investor 1999.0 NaN telecom, investments NaN NaN http://www.forbes.com/profile/rostam-azizi/ http://en.wikipedia.org/wiki/Vodacom_Tanzania http://www.thecitizen.co.tz/News/Rostam--Dewji... NaN
2401 2014 Tory Burch 1565 United States USA 1.0 self-made founder non-finance female 47.0 ... founder 2004.0 NaN fashion NaN NaN http://en.wikipedia.org/wiki/J._Christopher_Burch http://www.vanityfair.com/news/2007/02/tory-bu... NaN NaN
734 2014 Fred Chang 1565 United States USA 1.0 self-made founder non-finance male 57.0 ... founder 2001.0 NaN online retailing NaN NaN http://en.wikipedia.org/wiki/Newegg http://www.newegg.com/Info/FactSheet.aspx http://www.forbes.com/sites/andreanavarro/2014... NaN
171 2014 Angela Bennett 1565 Australia AUS 1.0 inherited inherited female 69.0 ... relation 1955.0 NaN mining inherited from father shared fortune with brother http://www.forbes.com/profile/angela-bennett/ NaN NaN NaN
748 2014 Fu Kwan 1565 China CHN 1.0 self-made self-made finance male 56.0 ... chairman 1990.0 NaN diversified NaN NaN http://www.forbes.com/profile/fu-kwan/ http://www.macrolink.com.cn/en/AboutBig.aspx NaN NaN
2107 2014 Ryan Kavanaugh 1565 United States USA 1.0 self-made founder non-finance male 39.0 ... founder 2004.0 NaN Movies NaN NaN http://en.wikipedia.org/wiki/Ryan_Kavanaugh http://en.wikipedia.org/wiki/Relativity_Media http://www.vanityfair.com/news/2010/03/kavanau... NaN
1783 2014 O. Francis Biondi 1565 United States USA 1.0 self-made self-made finance male 49.0 ... founder 1995.0 NaN hedge fund NaN NaN http://www.forbes.com/profile/o-francis-biondi/ http://www.forbes.com/sites/nathanvardi/2014/0... NaN NaN
1371 2014 Lam Fong Ngo 1565 Macau MAC 1.0 self-made self-made finance female NaN ... Vice Chairman 1997.0 NaN casinos NaN NaN http://www.forbes.com/profile/david-chow-1/ http://www.macaulegend.com/html/about_mileston... Macau Legend to roll the dice on HK IPO; But l... NaN
702 2014 Feng Hailiang 1565 China CHN 1.0 self-made founder non-finance male 53.0 ... founder 1989.0 NaN copper processing & real estate NaN NaN http://www.forbes.com/profile/feng-hailiang/ http://www.hailiang.com/en/about_int.php NaN NaN

10 rows × 30 columns


In [14]:
# 'What is relationship to company'? And what are the most common relationships?

In [28]:
#top 10 most common relationships to company
df['relationshiptocompany'].value_counts().head(10)


Out[28]:
founder                                 1214
relation                                 945
owner                                     94
chairman                                  76
investor                                  36
Chairman and Chief Executive Officer      29
CEO                                       16
president                                 13
ceo                                        9
Chairman                                   8
Name: relationshiptocompany, dtype: int64

In [19]:
# Most common source of wealth? Male vs. female?

In [18]:
# Most common source of wealth? Male vs. female

In [83]:
print("The most common source of wealth is", df['sourceofwealth'].value_counts().head(1))
print("The most common source of wealth for males is", male['sourceofwealth'].value_counts().head(1))
print("The most common source of wealth for females is", female['sourceofwealth'].value_counts().head(1))

#need to figure out how to extract just the number nd not the data type 'Name: sourceofwealth, dtype: int64'


The most common source of wealth is real estate    107
Name: sourceofwealth, dtype: int64
The most common source of wealth for males is real estate    100
Name: sourceofwealth, dtype: int64
The most common source of wealth for females is diversified    9
Name: sourceofwealth, dtype: int64

Given the richest person in a country, what % of the GDP is their wealth?


In [19]:
richest = df[df['citizenship'] == 'United States'].sort_values('rank').head(1)['networthusbillion'].to_dict()
# richest['networthusbillion']
richest[282]

## I JUST WANT THE VALUE -- 18.5.

## 16.77 TRILLION
US_GDP = 1.677 * (10^13)
US_GDP


Out[19]:
11.739

Add up the wealth of all of the billionaires in a given country (or a few countries) and then compare it to the GDP of the country, or other billionaires, so like pit the US vs India


In [ ]:

What are the most common industries for billionaires to come from? What's the total amount of billionaire money from each industry?


In [115]:
recent['sector'].value_counts().head(10)


Out[115]:
real estate        122
retail              78
construction        60
pharmaceuticals     55
media               50
banking             47
hedge funds         44
oil                 40
software            39
private equity      23
Name: sector, dtype: int64

In [119]:
df.groupby('sector')['networthusbillion'].sum()


Out[119]:
sector
  Oil refining                   57.8
 Communications                  88.9
 Finance                        112.8
 Oil refining                    45.2
 Software                       153.2
 casinos                         39.0
 fashion                         45.9
 finance                         41.5
 retail                          66.5
 software                        80.0
 technology                     126.6
Banking                          13.3
Fashion                          70.6
GPS technology                    4.1
HR consulting                     6.0
IT Consulting                     2.4
Star Wars                         9.9
advertising                      21.4
aerospace and defense             5.1
agribusiness                      7.2
agriculteral                      2.4
agricultural products             5.5
agriculture                       9.6
aigriculture                      2.5
air compressors                   1.6
aircraft leasing                 10.3
airline                           4.6
airplanes                         3.2
airport                           3.9
airport maintenance               6.4
                                ...  
trade investment                  9.5
trading                           2.5
trading company                   4.3
transportation                   18.5
travel company                   12.2
truck stop                        1.5
truck stops                       3.6
trucking                          2.2
trucking                          2.1
trucking and logistics            2.2
uniforms                          1.8
utilities                        11.0
utilities/financial services      5.1
vacuum cleaners                   4.5
venture capitalist               40.3
video games                       7.9
video technology                  2.7
waste management                  7.6
watch retail                      1.1
watches                           3.5
web broadcasting                  4.0
wind energy                       3.7
wine                              1.7
wine and spirits                  3.3
winter jackets                    1.4
wireless products                 2.7
wool                              1.0
wrestling promotion               1.2
yogurt                            1.4
zippers                           3.5
Name: networthusbillion, dtype: float64

How many self made billionaires vs. others?


In [29]:
(recent['selfmade'] == 'self-made').value_counts()


Out[29]:
True     1146
False     507
Name: selfmade, dtype: int64

How old are billionaires?


In [47]:
# recent['age'].value_counts().sort_values()
print("The average billionnaire is", round(recent['age'].mean()), "years old.")


The average billionnaire is 63.0 years old.

How old are billionaires self made vs. non self made?


In [82]:
df.groupby('selfmade')['age'].mean()


Out[82]:
selfmade
inherited    54.912000
self-made    59.474576
Name: age, dtype: float64

In [ ]:
# or different industries?

In [84]:
df.groupby('sector')['age'].mean()


Out[84]:
sector
  Oil refining                  69.400000
 Communications                 63.666667
 Finance                        74.125000
 Oil refining                   62.666667
 Software                       47.666667
 casinos                        73.500000
 fashion                        57.750000
 finance                        61.600000
 retail                         55.000000
 software                       58.666667
 technology                     39.200000
Banking                         49.250000
Fashion                         71.000000
GPS technology                  70.500000
HR consulting                   71.500000
IT Consulting                   61.000000
Star Wars                       58.666667
advertising                     68.250000
aerospace and defense           72.500000
agribusiness                    56.500000
agriculteral                    59.000000
agricultural products           89.500000
agriculture                     48.800000
aigriculture                    52.500000
air compressors                 51.000000
aircraft leasing                64.000000
airline                         47.000000
airplanes                       27.500000
airport                         53.500000
airport maintenance             61.666667
                                  ...    
trade investment                63.500000
trading                               NaN
trading company                 35.000000
transportation                  69.750000
travel company                  69.200000
truck stop                      60.000000
truck stops                           NaN
trucking                        32.500000
trucking                        82.000000
trucking and logistics          76.000000
uniforms                        66.000000
utilities                       63.500000
utilities/financial services    85.000000
vacuum cleaners                 66.000000
venture capitalist              52.066667
video games                     48.000000
video technology                72.000000
waste management                61.250000
watch retail                    70.000000
watches                         72.000000
web broadcasting                47.500000
wind energy                     62.000000
wine                            71.000000
wine and spirits                71.000000
winter jackets                  52.000000
wireless products               35.000000
wool                             0.000000
wrestling promotion             68.000000
yogurt                          42.000000
zippers                         51.500000
Name: age, dtype: float64

In [49]:
#youngest billionnaires 
recent.sort_values('age').head(10)


Out[49]:
year name rank citizenship countrycode networthusbillion selfmade typeofwealth gender age ... relationshiptocompany foundingdate gdpcurrentus sourceofwealth notes notes2 source source_2 source_3 source_4
1838 2014 Perenna Kei 1284 Hong Kong HKG 1.3 inherited inherited female 24.0 ... relation 1996.0 NaN real estate inherited from father NaN http://en.wikipedia.org/wiki/Perenna_Kei http://www.loganestate.com/en/about.aspx?ftid=294 NaN NaN
605 2014 Dustin Moskovitz 202 United States USA 6.8 self-made founder non-finance male 29.0 ... founder 2004.0 NaN Facebook NaN NaN http://en.wikipedia.org/wiki/Dustin_Moskovitz http://www.forbes.com/profile/dustin-moskovitz/ https://www.facebook.com/facebook/info?tab=pag... NaN
1586 2014 Mark Zuckerberg 21 United States USA 28.5 self-made founder non-finance male 29.0 ... founder 2004.0 NaN Facebook NaN NaN http://www.forbes.com/profile/mark-zuckerberg/ NaN NaN NaN
189 2014 Anton Kathrein, Jr. 1270 Germany DEU 1.4 inherited inherited male 29.0 ... relation 1919.0 NaN antennas 3rd generation NaN http://www.forbes.com/profile/anton-kathrein-jr/# NaN NaN NaN
602 2014 Drew Houston 1372 United States USA 1.2 self-made founder non-finance male 30.0 ... founder 2007.0 NaN Dropbox NaN NaN http://en.wikipedia.org/wiki/Drew_Houston http://en.wikipedia.org/wiki/Dropbox_(service) http://www.forbes.com/profile/drew-houston/ NaN
54 2014 Albert von Thurn und Taxis 1092 Germany DEU 1.6 inherited inherited male 30.0 ... relation 1615.0 NaN diversified monopoly on postal service in germany, nationa... two older sisters, did not inherit title becau... http://en.wikipedia.org/wiki/Thurn_und_Taxis http://en.wikipedia.org/wiki/Albert,_12th_Prin... NaN NaN
618 2014 Eduardo Saverin 367 Brazil BRA 4.1 self-made founder non-finance male 31.0 ... founder 2004.0 NaN Facebook NaN NaN http://en.wikipedia.org/wiki/Eduardo_Saverin http://www.bloomberg.com/news/articles/2012-05... NaN NaN
2151 2014 Scott Duncan 215 United States USA 6.3 inherited inherited male 31.0 ... relation 1968.0 NaN pipelines inherited from father NaN http://en.wikipedia.org/wiki/Scott_Duncan_(bus... http://www.forbes.com/profile/dannine-avara/ NaN NaN
2559 2014 Yang Huiyan 196 China CHN 6.9 inherited inherited female 32.0 ... relation 1997.0 NaN real estate inherited from father NaN http://en.wikipedia.org/wiki/Yang_Huiyan NaN NaN NaN
1569 2014 Marie Besnier Beauvalot 642 France FRA 2.7 inherited inherited female 33.0 ... relation 1933.0 NaN cheese inherited from father oldest brother is CEO http://www.forbes.com/profile/emmanuel-besnier/ http://en.wikipedia.org/wiki/Lactalis NaN NaN

10 rows × 30 columns


In [50]:
#oldest billionnaires 
recent.sort_values('age', ascending =False).head(10)


Out[50]:
year name rank citizenship countrycode networthusbillion selfmade typeofwealth gender age ... relationshiptocompany foundingdate gdpcurrentus sourceofwealth notes notes2 source source_2 source_3 source_4
516 2014 David Rockefeller, Sr. 580 United States USA 2.9 inherited inherited male 98.0 ... relation 1870.0 NaN oil, banking family made most of fortune in the late 19th a... NaN http://en.wikipedia.org/wiki/David_Rockefeller http://en.wikipedia.org/wiki/Standard_Oil http://en.wikipedia.org/wiki/Rockefeller_family NaN
1277 2014 Karl Wlaschek 305 Austria AUT 4.8 self-made founder non-finance male 96.0 ... founder 1953.0 NaN retail NaN NaN http://en.wikipedia.org/wiki/BILLA http://en.wikipedia.org/wiki/Karl_Wlaschek https://www.billa.at/Footer_Nav_Seiten/Geschic... NaN
1328 2014 Kirk Kerkorian 328 United States USA 4.5 self-made self-made finance male 96.0 ... investor 1924.0 NaN casinos, investments purchased in 1969 NaN http://en.wikipedia.org/wiki/Kirk_Kerkorian http://www.forbes.com/profile/kirk-kerkorian/ PROFILE: Las Vegas billionaire amassed his wea... NaN
921 2014 Henry Hillman 687 United States USA 2.5 inherited inherited male 95.0 ... relation 1942.0 NaN investments inherited from father NaN http://www.forbes.com/profile/henry-hillman/ http://en.wikipedia.org/wiki/Calgon_Carbon NaN NaN
666 2014 Erika Pohl-Stroher 1154 Germany DEU 1.5 inherited inherited female 95.0 ... relation 1880.0 NaN hair products 3rd generation 23% stake in the company http://www.forbes.com/profile/erika-pohl-stroher/ http://en.wikipedia.org/wiki/Wella NaN NaN
2292 2014 Sulaiman Al Rajhi 931 Saudi Arabia SAU 1.9 self-made self-made finance male 94.0 ... founder 1957.0 NaN banking NaN NaN http://en.wikipedia.org/wiki/Al-Rajhi_Bank http://www.alrajhibank.com.sa/ar/investor-rela... http://www.alrajhibank.com.sa/ar/about-us/page... NaN
181 2014 Anne Cox Chambers 58 United States USA 15.5 inherited inherited female 94.0 ... relation 1898.0 NaN media inherited from brother NaN http://en.wikipedia.org/wiki/Anne_Cox_Chambers http://www.forbes.com/lists/2010/10/billionair... http://www.nytimes.com/2007/05/30/business/med... NaN
1275 2014 Karl Albrecht 23 Germany DEU 25.0 self-made executive male 94.0 ... relation 1914.0 NaN retail (split from Aldi Nord in 1966, but both branch... took over mother's single grocerty store http://en.wikipedia.org/wiki/Karl_Albrecht http://www.bloomberg.com/news/articles/2014-07... http://aldiuscareers.com/about-aldi/history NaN
119 2014 Aloysio de Andrade Faria 483 Brazil BRA 3.3 inherited inherited male 93.0 ... relation 1925.0 NaN banking inherited from father NaN http://en.wikipedia.org/wiki/Aloysio_de_Andrad... http://en.wikipedia.org/wiki/Banco_da_Lavoura_... http://www.forbes.com/profile/aloysio-de-andra... NaN
2487 2014 Wang Yung-Tsai 520 Taiwan Taiwan 3.1 self-made founder non-finance male 93.0 ... founder 1954.0 NaN plastics NaN NaN http://www.forbes.com/profile/wang-yung-tsai/ What's good for the goose South China Morning ... NaN NaN

10 rows × 30 columns


In [ ]:
#Age distribution - maybe make a graph about it?

In [65]:
import matplotlib.pyplot as plt
%matplotlib inline
# This will scream we don't have matplotlib.
his = df['age'].hist(range=[0, 100])


his.set_title('Distribution of Age Amongst Billionaires')
his.set_xlabel('Age(years)')
his.set_ylabel('# of Billionnaires')


Out[65]:
<matplotlib.text.Text at 0x10787d2b0>

In [ ]:
# Maybe just made a graph about how wealthy they are in general?

In [77]:
import matplotlib.pyplot as plt
%matplotlib inline
# This will scream we don't have matplotlib.


his = df['networthusbillion'].hist(range=[0, 45])


his.set_title('Distribution of Wealth Amongst Billionaires')
his.set_xlabel('Wealth(Billions)')
his.set_ylabel('# of Billionnaires')


Out[77]:
<matplotlib.text.Text at 0x1081885f8>

Maybe plot their net worth vs age (scatterplot) Make a bar graph of the top 10 or 20 richest


In [79]:
recent.plot(kind='scatter', x='networthusbillion', y='age')


Out[79]:
<matplotlib.axes._subplots.AxesSubplot at 0x107df8f60>

In [81]:
recent.plot(kind='scatter', x='age', y='networthusbillion')


Out[81]:
<matplotlib.axes._subplots.AxesSubplot at 0x1083d4400>

In [ ]: