Question

我需要遍历此数据框的'Grade'列，并将"1"，"2"或"K"的条目替换为"1/2"和{{1 }}或"3"与"4"

"3/4"

这是DF：

for i in kids_df:
    if kids_df['G'] == 1 or 2:
        kids_df['G'] = kids_df['Grade'].replace('1/2')

我正在寻找的结果：

Name    M/F Grade   Size    Notes
0   Peter Parker    M   2   YM  Baughman
1   Tony Stark  M   1   YL  Baughman
2   Steve Rogers    M   K   YM  Baughman
3   Donald Blake    M   2   YM  Baughman
4   Bruce Banner    M   3   YM  Baughman

Answer 1

尝试使用np.where：

df['Grade'] = np.where(df['Grade'].isin(['1', '2', 'K']), '1/2', '3/4')
print(df)

或使用双str.replace：

df['Grade'] = df['Grade'].str.replace('1|2|K', '1/2').str.replace('3|4', '3/4')
print(df)

或在字典中使用replace：

df['Grade'] = df['Grade'].replace({'1|2|K': '1/2', '3|4': '3/4'}, regex=True)
print(df)

它们全部输出：

           Name M/F Grade Size     Notes
0  Peter Parker   M   1/2   YM  Baughman
1    Tony Stark   M   1/2   YL  Baughman
2  Steve Rogers   M   1/2   YM  Baughman
3  Donald Blake   M   1/2   YM  Baughman
4  Bruce Banner   M   3/4   YM  Baughman

Answer 2

我们可以做replace

kids_df['G']=kids_df['G'].replace({1:'1/2',2:'1/2',3:'3/4',4:'3/4'})

遍历大熊猫数据框并替换整个

2 个答案: