import numpy as np
import pandas as pd

df=pd.DataFrame([[1.4,np.nan],[7.1,-4.5],
                [np.nan,np.nan],[0.75,-1.3]],
                index=['a','b','c','d'],
                columns=['one','two'])
df

	one	two
a	1.40	NaN
b	7.10	-4.5
c	NaN	NaN
d	0.75	-1.3

#默认按列求和
df.sum()

one    9.25
two   -5.80
dtype: float64

# 按行求和
df.sum(axis=1)   # skipna = False

a    1.40
b    2.60
c    0.00
d   -0.55
dtype: float64

df.idxmax()

one    b
two    d
dtype: object

df.cumsum()

	one	two
a	1.40	NaN
b	8.50	-4.5
c	NaN	NaN
d	9.25	-5.8

# 汇总统计
df.describe()

	one	two
count	3.000000	2.000000
mean	3.083333	-2.900000
std	3.493685	2.262742
min	0.750000	-4.500000
25%	1.075000	-3.700000
50%	1.400000	-2.900000
75%	4.250000	-2.100000
max	7.100000	-1.300000

s1 = pd.Series(['a','a','b','c']*4)
s1

0     a
1     a
2     b
3     c
4     a
5     a
6     b
7     c
8     a
9     a
10    b
11    c
12    a
13    a
14    b
15    c
dtype: object

s1.describe()

count     16
unique     3
top        a
freq       8
dtype: object