In [51]:
import pandas as pd
import matplotlib.pyplot as plt
%matplotlib inline

1. Open your dataset up using pandas in a Jupyter notebook


In [52]:
df = pd.read_csv("India.csv")

In [53]:
df.columns


Out[53]:
Index(['id', 'name', 'company_type', 'locations', 'quality',
       'company_size(upper limit)', 'follower_count', 'high_concept',
       'markets', 'angellist_url'],
      dtype='object')

2. Do a .head() to get a feel for your data


In [54]:
df.head()


Out[54]:
id name company_type locations quality company_size(upper limit) follower_count high_concept markets angellist_url
0 1194302 Bhubaneswar Buzz Marketing Bhubaneswar 0 10 1 Social Media Marketing Startup with Odisha Focus Social Media Marketing, Brand Marketing, Promo... https://angel.co/bhubaneswar-buzz-1
1 1193791 Rice Bar Food Bangalore 0 10 1 Rice Bar ' An exotic Rice Adventure' Food and Beverages, Specialty Foods, Organic Food https://angel.co/rice-bar
2 1193420 vipra Supply Chain Bangalore 0 10 1 Creating an efficient supply chain for agricul... Supply Chain Management https://angel.co/vipra
3 1193385 Blackbuck Insights Big Data Chennai 0 10 3 Providing cost effective solutions using niche... Business Intelligence, Big Data Analytics, Dat... https://angel.co/blackbuck-insights
4 1193247 toto Marketing New Delhi 0 10 1 test Private Social Networking https://angel.co/toto-8

3. Write down 12 questions to ask your data, or 12 things to hunt for in the data

  1. Count the number of startups in each cities ?
  2. Find the city in which the highest number of startups in India.
  3. Find the domain in which the highest number of startups are from
  4. Find the domains in which the lowest number of startups are from
  5. How many startups are from the E-Commerce domain?
  6. How many startups are from media ?
  7. Count the number of startups with highest rating.
  8. Describe the company size of Bangalore-based startups
  9. Which company has the highest number of followers on Angel list ?
  10. Which company has the highest strength ?
  11. Count the strength of startups in Media domain
  12. What's the average size of a startup in India as given by this Angel list data set ?

1. Count the number of startups in each cities ?


In [55]:
df["locations"].value_counts()


Out[55]:
Bangalore        30
New Delhi        20
Mumbai           14
Pune              7
Gurgaon           5
Chennai           5
Hyderabad         3
Noida             3
India             3
Bhubaneswar       2
Chandigarh        2
Jodhpur           1
Bhopal            1
Ludhiana          1
Delhi             1
Jaipur            1
Visakhapatnam     1
Calcutta          1
Kochi             1
Name: locations, dtype: int64

2. Find the city in which the highest number of startups in India.


In [56]:
df["locations"].value_counts().head(1)


Out[56]:
Bangalore    30
Name: locations, dtype: int64

3. Find the domain in which the highest number of startups are from


In [57]:
df['company_type'].value_counts()


Out[57]:
E-Commerce               19
Mobile                   10
Marketing                10
Healthcare Technology     5
Web Development           4
Education                 4
Software                  4
HR                        4
Travel and Tourism        4
Food                      4
Services                  3
Lifestyle                 3
Finance                   3
Games                     2
Big Data                  2
Housing                   2
AI                        2
Automotive                2
Agriculture               2
Media                     2
Logistics                 2
Pharmaceuticals           1
IT                        1
UI Design                 1
Aerospace                 1
Social Media              1
Energy                    1
Supply Chain              1
Footwear                  1
Legal Tech                1
Name: company_type, dtype: int64

In [58]:
df['company_type'].value_counts().head(1)


Out[58]:
E-Commerce    19
Name: company_type, dtype: int64

4. Find the domains in which the lowest number of startups are from


In [59]:
df['company_type'].value_counts().tail(9)


Out[59]:
Pharmaceuticals    1
IT                 1
UI Design          1
Aerospace          1
Social Media       1
Energy             1
Supply Chain       1
Footwear           1
Legal Tech         1
Name: company_type, dtype: int64

5. How many startups are from the E-Commerce domain?


In [60]:
print("There are", len(df[df['company_type'] =='E-Commerce']),"startups in E-commerce")


There are 19 startups in E-commerce

6. How many startups are from media ?


In [61]:
print("There are", len(df[df['company_type'] =='Media']),"startups in media")


There are 2 startups in media

7. Count the number of startups with highest rating.


In [62]:
df[df['quality'] == 4]


Out[62]:
id name company_type locations quality company_size(upper limit) follower_count high_concept markets angellist_url
55 1185339 Compared E-Commerce Bangalore 4 50 2 Personal Shopping Assistant on Mobile E-Commerce, Mobile Commerce https://angel.co/compared
63 1185000 iamwire Software Gurgaon 4 10 1 A platform assisting technology innovations Startups, Technology https://angel.co/iamwire-3
90 1180544 SendThruMe Logistics Bangalore 4 10 1 Send goods with travelers and save on shipping... Logistics https://angel.co/sendthrume

In [63]:
print("There are", len(df[df['quality'] == 4]),"startups with the highest rating.")


There are 3 startups with the highest rating.

8. Describe the company size of Bangalore-based startups


In [64]:
blr = df[df['locations'] =='Bangalore']
blr


Out[64]:
id name company_type locations quality company_size(upper limit) follower_count high_concept markets angellist_url
1 1193791 Rice Bar Food Bangalore 0 10 1 Rice Bar ' An exotic Rice Adventure' Food and Beverages, Specialty Foods, Organic Food https://angel.co/rice-bar
2 1193420 vipra Supply Chain Bangalore 0 10 1 Creating an efficient supply chain for agricul... Supply Chain Management https://angel.co/vipra
5 1192761 Hiteshi Software Bangalore 0 200 1 Turnkey IT Projects Mobile, Enterprise Software, Web Design, Mobil... https://angel.co/hiteshi-1
13 1192205 Smart Living Retail E-Commerce Bangalore 3 10 1 Storage Solutions for homes Retail, E-Commerce Platforms, Trade Platform https://angel.co/smart-living-retail
17 1191976 Aquagenics R&D India Lifestyle Bangalore 2 100 1 Clean, healthy water for improved hair and skin. Retail, Lifestyle Products, Health and Wellness https://angel.co/aquagenics-r-d-india
21 1190665 Kaarvaan Solutions E-Commerce Bangalore 2 50 1 Creating value and bringing change by connecti... Mobile, Social Media, E-Commerce https://angel.co/kaarvaan-solutions
22 1190540 Geeks of Gaming Games Bangalore 3 50 1 An innovative gaming company aimed to introduc... Games, Video Games, Mobile Games https://angel.co/geeks-of-gaming
23 1189939 Phoenix Compliance Healthcare Technology Bangalore 2 200 1 Healthcare Entities can go paperless,Physician... Health Care, Health Care Information Technolog... https://angel.co/phoenix-compliance
27 1188814 Mean Metal Motors Automotive Bangalore 3 50 2 Premium Performance Electric Vehicles. Clean Energy, Automotive, Electric Vehicles, H... https://angel.co/mean-metal-motors-2
28 1188783 Jobs Galore HR Bangalore 2 10 1 One Stop Shop for Career Advice Career Management, Career Planning https://angel.co/jobs-galore-1
32 1188746 pumpkart E-Commerce Bangalore 2 50 1 Pumpkart has been envisioned to be the No.1 co... E-Commerce Platforms https://angel.co/pumpkart-1
33 1188665 Official Gates Technologies Mobile Bangalore 2 50 1 Mobile App Development Mobile, Android, Web Development, Mobile Appli... https://angel.co/official-gates-technologies
39 1188448 SecondScreen Aerospace Bangalore 3 10 1 Wireless Inflight Entertainment Aerospace, Travel & Tourism, Ecommerce, Mariti... https://angel.co/secondscreen-1
42 1187616 Liveongo-Artivatic AI Bangalore 2 50 0 AI focused Instant, Predictive & Personalize I... Artificial Intelligence https://angel.co/liveongo-artivatic
48 1185510 Artivatic Hiring AI Bangalore 2 10 0 AI focused Instant, Predictive & Personalize I... Intelligent Systems, Artificial Intelligence https://angel.co/artivatic-hiring
50 1185475 MobiCollector Mobile Bangalore 2 10 1 We developed App like Cable TV Operators, EMI ... Mobile, Mobile Payments https://angel.co/mobicollector
51 1185461 www.plexcel.com Software Bangalore 2 10 1 We are web magicians who makes brands live up ... Software https://angel.co/www-plexcel-com
52 1185403 NXT International Trade Energy Bangalore 2 50 1 Enabling business in India Specialty Foods, Waste Management, Renewable E... https://angel.co/nxt-international-trade
55 1185339 Compared E-Commerce Bangalore 4 50 2 Personal Shopping Assistant on Mobile E-Commerce, Mobile Commerce https://angel.co/compared
61 1185040 Capsten Technologies E-Commerce Bangalore 2 10 1 Web and Mobile Application Development E-Commerce, Android, Web Development, Mobile A... https://angel.co/capsten-technologies
65 1184899 Provab Technosoft Travel and Tourism Bangalore 2 10 1 Travel Technology Solutions Travel & Tourism https://angel.co/provab-technosoft-10
67 1184735 Story Housing Bangalore 3 10 1 Better Living Spaces in Urban Hotspots Real Estate, Technology https://angel.co/story-6
76 1182853 Pocketin E-Commerce Bangalore 3 10 3 Pocketin is an online platform to sell/buy qua... E-Commerce, Consumer Electronics https://angel.co/pocketin-1
84 1182289 Fermedicius Labs Lifestyle Bangalore 2 10 1 Ingenious products from real farms which are E... Food and Beverages, Novelty Stores, Health and... https://angel.co/fermedicius-labs
89 1180560 Easoftech Solutions E-Commerce Bangalore 2 10 1 Solutions that help our clients streamline ope... B2B, Ecommerce https://angel.co/easoftech-solutions
90 1180544 SendThruMe Logistics Bangalore 4 10 1 Send goods with travelers and save on shipping... Logistics https://angel.co/sendthrume
91 1180529 FuGenX Technologies Mobile Bangalore 2 10 1 mobile apps design development Mobile Application https://angel.co/fugenx-technologies-30
99 1180054 Blimps India aerial technologies Marketing Bangalore 2 10 1 aerial RC blimps which can be used for events,... Advertising, Events https://angel.co/blimps-india-aerial-technolog...
100 1179975 Awnics Tech. Web Development Bangalore 3 10 1 Create Solution to simplify Healthcare access ... Web Development, Mobile Application https://angel.co/awnics-tech
101 1179946 InnoCenter Agriculture Bangalore 2 10 1 Bringing mechanism to Farmers, Bringing farmin... Retail, Industrial Automation, Organic, Home &... https://angel.co/innocenter

9. Which company has the highest strength ?


In [90]:
columns_want = df[['name','company_size(upper limit)','company_type']]
columns_want
columns_want.sort_values('company_size(upper limit)', ascending=False).head(2)


Out[90]:
name company_size(upper limit) company_type
31 Travel Insurance - Policybazaar 1000 Finance
18 FundsIndia 500 E-Commerce

10. Which company has the highest number of followers on Angel list ?


In [72]:
df.sort_values('follower_count', ascending=False).head(1)


Out[72]:
id name company_type locations quality company_size(upper limit) follower_count high_concept markets angellist_url
43 1186777 i&We Engagements Education Calcutta 3 50 7 Education Technology with a Touch Of Human Lev... Education, New Product Development, Skill Asse... https://angel.co/i-we-engagements-1

In [83]:
print("The company with the highest follower on Angel list is:")
df.groupby('name')['follower_count'].sum().sort_values(ascending=False).head(1)


The company with the highest follower on Angel list is:
Out[83]:
name
i&We Engagements     7
Name: follower_count, dtype: int64

11. Count the strength of startups in Media domain


In [86]:
media = df[df['company_type'] =='Media']
media


Out[86]:
id name company_type locations quality company_size(upper limit) follower_count high_concept markets angellist_url
7 1192747 WikiMonks Media Visakhapatnam 0 50 1 Multi Platform Media/News/Publishing Digital Media, Publishing, News, Technology https://angel.co/wikimonks
57 1185226 Dextra Media New Delhi 3 50 1 Find. Or be found. Film, Musicians, Designers, Writers https://angel.co/dextra

In [88]:
print("The total strength of startups in media domain is", media['company_size(upper limit)'].sum())


The total strength of startups in media domain is 100

12. What's the average size of a startup in India as given by this Angel list data set ?


In [89]:
df['company_size(upper limit)'].describe()


Out[89]:
count     102.000000
mean       47.843137
std       121.211928
min        10.000000
25%        10.000000
50%        10.000000
75%        50.000000
max      1000.000000
Name: company_size(upper limit), dtype: float64

13. Describe the number of startups in each domain based on location


In [75]:
df.groupby("company_type")['locations'].value_counts()


Out[75]:
company_type        locations    
AI                  Bangalore        2
Aerospace           Bangalore        1
Agriculture         Bangalore        1
                    Pune             1
Automotive          Bangalore        1
                    New Delhi        1
Big Data            Chennai          1
                    Ludhiana         1
E-Commerce          Bangalore        7
                    New Delhi        3
                    Chennai          2
                    Mumbai           2
                    Pune             2
                    Bhopal           1
                    Hyderabad        1
                    Kochi            1
Education           New Delhi        2
                    Calcutta         1
                    Hyderabad        1
Energy              Bangalore        1
Finance             Mumbai           2
                    Gurgaon          1
Food                Bangalore        1
                    Hyderabad        1
                    Mumbai           1
                    New Delhi        1
Footwear            Noida            1
Games               Bangalore        1
                    Noida            1
HR                  New Delhi        2
                                    ..
Marketing           Gurgaon          1
                    Mumbai           1
                    Pune             1
Media               New Delhi        1
                    Visakhapatnam    1
Mobile              Bangalore        3
                    Mumbai           2
                    Chennai          1
                    Delhi            1
                    Gurgaon          1
                    India            1
                    New Delhi        1
Pharmaceuticals     New Delhi        1
Services            Chennai          1
                    India            1
                    Mumbai           1
Social Media        Jodhpur          1
Software            Bangalore        2
                    Gurgaon          1
                    Pune             1
Supply Chain        Bangalore        1
Travel and Tourism  Bangalore        1
                    India            1
                    Mumbai           1
                    Noida            1
UI Design           Pune             1
Web Development     Bangalore        1
                    Chandigarh       1
                    New Delhi        1
                    Pune             1
Name: locations, dtype: int64

Graph 1 Location Plot


In [94]:
df['locations'].value_counts().plot(kind='bar',x='locations', color='red')


Out[94]:
<matplotlib.axes._subplots.AxesSubplot at 0x7941c30>

2. Graph 2. Domain Plot


In [95]:
df['company_size(upper limit)'].value_counts().plot(kind='bar',x='company_type', color='orange')


Out[95]:
<matplotlib.axes._subplots.AxesSubplot at 0x8a9ad30>

In [98]:
df.groupby("locations")['company_type'].head(5).value_counts().plot(kind='bar',x='company_type', color='green')


Out[98]:
<matplotlib.axes._subplots.AxesSubplot at 0x8d97950>

In [ ]: