子集pandas dataframe时忽略KeyError

问题描述

我有一个熊猫数据框df，其列为city1，city2，city3，city4，city5.我有一个列表my_cities = ["city1"，"city3"，"city10"].我想根据my_cities中的列对df进行子集设置.

I have a pandas dataframe df with columns city1, city2,city3,city4,city5. I have a list my_cities = ["city1","city3","city10"]. I want to subset df according to the columns in my_cities.When I do,

my_cities = ["city1"，"city3"，"city10"]

my_cities = ["city1","city3","city10"]

df_my_cities = df [my_cities]

df_my_cities = df[my_cities]

我收到错误KeyError:"['city10']不在索引中"

I get the error KeyError: "['city10'] not in index"

如果my_cities中的元素不在df中，我如何告诉代码继续执行?

How can I tell the code to keep proceeding if an element from my_cities in not in df?

推荐答案

您可以使用 intersection 在所有列和list之间:

df_my_cities = df[df.columns.intersection(my_cities)]

示例:

df = pd.DataFrame({'city1':['s', 'e'],
                   'city2':['e','f'],
                   'city3':['f','g'],
                   'city4':['r','g'],
                   'city5':['t','m']})

print (df)
  city1 city2 city3 city4 city5
0     s     e     f     r     t
1     e     f     g     g     m

my_cities = ["city1","city3","city10"]
df_my_cities = df[df.columns.intersection(my_cities)]
print (df_my_cities)
  city1 city3
0     s     f
1     e     g

或者 numpy.intersect1d :

df_my_cities = df[np.intersect1d(df.columns, my_cities)]
print (df_my_cities)
  city1 city3
0     s     f
1     e     g

这篇关于子集pandas dataframe时忽略KeyError的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持！