[Visualización del análisis de datos] Cálculo matemático simple de DataFrame

import numpy as np
import pandas as pd
from pandas import Series, DataFrame
s1 = Series([1,2,3],index=['A','B','C'])
s1
A    1
B    2
C    3
dtype: int64
s2 = Series([4,5,6,7],index=['B','C','D','E'])
s2
B    4
C    5
D    6
E    7
dtype: int64
# Series相加(对应index的value相加)
# nan和任何数相加都为nan
s1 + s2
A    NaN
B    6.0
C    8.0
D    NaN
E    NaN
dtype: float64

Operación de marco de datos

df1 = DataFrame(np.arange(4).reshape(2,2), index=['A','B'], columns=['BJ','SH'])
df1
BJ SH
UNA 0 0 1
si 2 3
df2 = DataFrame(np.arange(9).reshape(3,3), index=['A','B','C'], columns=['BJ','GZ','SH'])
df2
BJ GZ SH
UNA 0 0 1 2
si 3 4 4 5 5
C 6 6 7 7 8
# 加法,对应索引的值相加(nan加什么都是nan)
df1 + df2
BJ GZ SH
UNA 0.0 NaN 3.0
si 5.0 NaN 8.0
C NaN NaN NaN
df3 = DataFrame([[1,2,3],[4,5,np.nan],[7,8,9]], index=['A','B','C'], columns=['c1','c2','c3'])
df3
c1 c2 c3
UNA 1 2 3.0
si 4 4 5 5 NaN
C 7 7 8 9.0
# 求和 默认列(此时求和会忽略nan)
df3.sum()
c1    12.0
c2    15.0
c3    12.0
dtype: float64
type(df3.sum())
pandas.core.series.Series
# 求和 行
df3.sum(axis=1)
A     6.0
B     9.0
C    24.0
dtype: float64
# 最小值 默认列
df3.min()
c1    1.0
c2    2.0
c3    3.0
dtype: float64
# 最小值 行
df3.min(axis=1)
A    1.0
B    4.0
C    7.0
dtype: float64
# 返回统计数据 平均值mean
df3.describe()
c1 c2 c3
contar 3.0 3.0 2.000000
media 4.0 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 4.0 5.0 6.000000
75% 5.5 6.5 7.500000
max 7.0 8.0 9.000000
df3
c1 c2 c3
UNA 1 2 3.0
si 4 4 5 5 NaN
C 7 7 8 9.0
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Origin blog.csdn.net/weixin_43469680/article/details/105616691
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