Files



In [1]:

    
import pandas as pd

df = pd.read_csv("https://raw.githubusercontent.com/plotly/datasets/master/school_earnings.csv")

Plot the data frame

Sources:



In [2]:

    
%matplotlib inline



In [3]:

    
df.plot()









    Out[3]:





<matplotlib.axes._subplots.AxesSubplot at 0x7fa5a1918c50>



In [4]:

    
df.style



In [19]:

    
df.sort_values(by=["Women"], ascending= 0)

	School	Women	Men	gap
0	MIT	94	152	58
1	Stanford	96	151	55
2	Harvard	112	165	53
3	U.Penn	92	141	49
4	Princeton	90	137	47
5	Chicago	78	118	40
6	Georgetown	94	131	37
7	Tufts	76	112	36
8	Yale	79	114	35
9	Columbia	86	119	33
10	Duke	93	124	31
11	Dartmouth	84	114	30
12	NYU	67	94	27
13	Notre Dame	73	100	27
14	Cornell	80	107	27
15	Michigan	62	84	22
16	Brown	72	92	20
17	Berkeley	71	88	17
18	Emory	68	82	14
19	UCLA	64	78	14
20	SoCal	72	81	9

	School	Women	Men	gap
2	Harvard	112	165	53
1	Stanford	96	151	55
0	MIT	94	152	58
6	Georgetown	94	131	37
10	Duke	93	124	31
3	U.Penn	92	141	49
4	Princeton	90	137	47
9	Columbia	86	119	33
11	Dartmouth	84	114	30
14	Cornell	80	107	27
8	Yale	79	114	35
5	Chicago	78	118	40
7	Tufts	76	112	36
13	Notre Dame	73	100	27
16	Brown	72	92	20
20	SoCal	72	81	9
17	Berkeley	71	88	17
18	Emory	68	82	14
12	NYU	67	94	27
19	UCLA	64	78	14
15	Michigan	62	84	22