在Python DataFrames中查找?

时间:2019-02-01 16:06:26

标签: python python-3.x pandas dataframe

我有一个数据框df1:

Month

1
3
March
April
2
4
5

我还有另一个数据框df2:

Month  Name

1       January
2       February
3       March
4       April
5       May

如果要用df2中的相应名称替换df1的整数值,可以使用哪种查找功能?

我想以此作为我的df1:

    Month

January
March
March
April
February
May

4 个答案:

答案 0 :(得分:5)

replace

df1.replace(dict(zip(df2.Month.astype(str),df2.Name)))
Out[76]: 
      Month
0   January
1     March
2     March
3     April
4  February
5     April
6       May

答案 1 :(得分:3)

您可以先使用pd.Series.map,然后再使用fillna。请注意将字符串映射为字符串,或者将数字映射为数字:

month_name = df2.set_index('Month')['Name']

df1['Month'] = pd.to_numeric(df1['Month'], errors='coerce').map(month_name)\
                 .fillna(df1['Month'])

print(df1)

      Month
0   January
1     March
2     March
3     April
4  February
5     April
6       May

您也可以使用pd.Series.replace,但这是often inefficient

答案 2 :(得分:1)

一种替代方法是将map与以下函数配合使用:

def repl(x, lookup=dict(zip(df2.Month.astype(str), df2.Name))):
    return lookup.get(x, x)

df['Month'] = df['Month'].map(repl)
print(df)

输出

      Month
0   January
1  February
2     March
3     April
4       May

答案 3 :(得分:1)

map与系列配合使用,只需确保您的dtypes匹配:

mapper = df2.set_index(df2['Month'].astype(str))['Name']
df1['Month'].map(mapper).fillna(df1['Month'])

输出:

0     January
1       March
2       March
3       April
4    February
5       April
6         May
Name: Month, dtype: object