pandas-12 数学计算操作df.sum()、df.min()、df.max()、df.decribe()

import numpy as np

import pandas as pd

from pandas import Series, DataFrame

s1 = Series([1, 2, 3], index=['A', 'B', 'C'])

print(s1)

'''

A    1

B    2

C    3

dtype: int64

'''

s2 = Series([4, 5, 6, 7], index=['B', 'C', 'D', 'E'])

print(s2)

'''

B    4

C    5

D    6

E    7

dtype: int64

'''

# 两个series进行相加，任何数字和nan相加都是nan

print(s1 + s2)

'''

A    NaN

B    6.0

C    8.0

D    NaN

E    NaN

dtype: float64

'''

# dataframe 的规则和series一样

df1 = DataFrame(np.arange(4).reshape(2, 2), index=['A', 'B'], columns=['bj', 'sh'])

print(df1)

'''

   bj  sh

A   0   1

B   2   3

'''

df2 = DataFrame(np.arange(9).reshape(3, 3), index=['A', 'B', 'C'], columns=['bj', 'sh', 'gz'])

print(df2)

'''

   bj  sh  gz

A   0   1   2

B   3   4   5

C   6   7   8

'''

print(df1 + df2)

'''

    bj  gz   sh

A  0.0 NaN  2.0

B  5.0 NaN  7.0

C  NaN NaN  NaN

'''

df3 = DataFrame([[1, 2, 3], [4, 5, np.nan], [7, 8, 9]], index=['A', 'B', 'C'], columns=['c1', 'c2', 'c3'])

print(df3)

'''

   c1  c2   c3

A   1   2  3.0

B   4   5  NaN

C   7   8  9.0

'''

# 按照每一列　相加，返回　

print(df3.sum())

'''

c1    12.0

c2    15.0

c3    12.0

dtype: float64

'''

#　指定　axis, 按照每一行相加

print(df3.sum(axis=1))

'''

A     6.0

B     9.0

C    24.0

dtype: float64

'''

print(df3.min())

'''

c1    1.0

c2    2.0

c3    3.0

dtype: float64

'''

print(df3.min(axis=1))

'''

A    1.0

B    4.0

C    7.0

dtype: float64

'''

print(df3.max())

# 打印出dataframe的数学信息

print(df3.describe())

print(type(df3.describe())) # <class 'pandas.core.frame.DataFrame'>

'''

        c1   c2        c3

count  3.0  3.0  2.000000

mean   4.0  5.0  6.000000

std    3.0  3.0  4.242641

min    1.0  2.0  3.000000

25%    2.5  3.5  4.500000

50%    4.0  5.0  6.000000

75%    5.5  6.5  7.500000

max    7.0  8.0  9.000000

'''