子查询

#coding=utf-8
import numpy as np
import pandas as pd

df1=pd.DataFrame({"city":["Chicago","SanFrancisco","Newyork"],
                  "rank":range(1,4)})
df2=pd.DataFrame({"city":["Chicago","Boston","Angles"],
                  "rank":range(1,4)})
print(df1)
'''
           city  rank
0       Chicago     1
1  SanFrancisco     2
2       Newyork     3
'''
print(df2)
'''
      city  rank
0  Chicago     1
1   Boston     2
2   Angles     3
'''


#举例1、子查询 isin 后面接 Seris
print(df1.loc[df1.city.isin(df2.city)])
'''
      city  rank
0  Chicago     1
'''

#举例2、子查询 isin 后面接 List
print(df1.loc[df1.city.isin(['Chicago','Newyork'])])
'''
      city  rank
0  Chicago     1
2  Newyork     3
'''

#举例3、isin 后也可以接DataFrame，需要两边的DataFrame列名，索引，值都一致时才会显示数据
print(df1[df1.isin(df2)])
'''
      city  rank
0  Chicago     1
1      NaN     2
2      NaN     3
'''

数据更新

tips=pd.read_csv("tips.csv").head()
print(tips)
'''
   total_bill   tip     sex smoker  day    time  size
0       16.99  1.01  Female     No  Sun  Dinner     2
1       10.34  1.66    Male     No  Sun  Dinner     3
2       21.01  3.50    Male     No  Sun  Dinner     3
3       23.68  3.31    Male     No  Sun  Dinner     2
4       24.59  3.61  Female     No  Sun  Dinner     4
'''

#举例1、将tip列的值小于2的值乘以2,  *=2
#先查询出tip列小于2的数据
print(tips.loc[tips.tip<2])
'''
   total_bill   tip     sex smoker  day    time  size
0       16.99  1.01  Female     No  Sun  Dinner     2
1       10.34  1.66    Male     No  Sun  Dinner     3
'''
#仅只显示tip列
print(tips.loc[tips.tip<2,"tip"])
'''
0    1.01
1    1.66
Name: tip, dtype: float64
'''
#最后将，tip列的值小于2的数据乘以2(结果再重新赋值给tip列)
tips.loc[tips.tip<2,"tip"]*=2
print(tips)
'''
   total_bill   tip     sex smoker  day    time  size
0       16.99  2.02  Female     No  Sun  Dinner     2
1       10.34  3.32    Male     No  Sun  Dinner     3
2       21.01  3.50    Male     No  Sun  Dinner     3
3       23.68  3.31    Male     No  Sun  Dinner     2
4       24.59  3.61  Female     No  Sun  Dinner     4
'''


#举例1、将tip列的值大于3.5的删除(即保留小于等于3.5)
print(tips.loc[tips.tip<=3.5])
tips=tips.loc[tips.tip<=3.5]
print(tips)
'''
   total_bill   tip     sex smoker  day    time  size
0       16.99  2.02  Female     No  Sun  Dinner     2
1       10.34  3.32    Male     No  Sun  Dinner     3
2       21.01  3.50    Male     No  Sun  Dinner     3
3       23.68  3.31    Male     No  Sun  Dinner     2
'''