我有以下數據表import pandas as pd dt = pd.DataFrame({'id_audience': ['Female 13-17', 'Female 18-20'], 'gender': ['female', 'female'], 'age_min': [13, 18], 'age_max': [17, 20]})我想擴展這個數據框，有一個額外的列 ( age)，并且age應該是 和 之間的age_min范圍age_max。最終結果將如下所示： dt = pd.DataFrame({'id_audience': ['Female 13-17', 'Female 13-17', 'Female 13-17', 'Female 13-17', 'Female 13-17', 'Female 18-20', 'Female 18-20', 'Female 18-20', ], 'gender': ['female', 'female', 'female', 'female', 'female', 'female', 'female', 'female'], 'age_min': [13, 13, 13, 13, 18, 18, 18, 18], 'age_max': [17, 17, 17, 17, 20, 20, 20, 20], 'age': [13, 14, 15, 16, 17, 18, 19, 20]})有任何想法嗎 ？
3 回答
搖曳的薔薇
TA貢獻1793條經驗 獲得超6個贊
也使用explode像@Wen，但在最小/最大年齡列上直接訪問范圍
dt.assign(
age=[np.arange(x, y+1) for x, y in zip(dt['age_min'], dt['age_max'])]
).explode('age').reset_index(drop=True)
id_audience gender age_min age_max age
0 Female 13-17 female 13 17 13
1 Female 13-17 female 13 17 14
2 Female 13-17 female 13 17 15
3 Female 13-17 female 13 17 16
4 Female 13-17 female 13 17 17
5 Female 18-20 female 18 20 18
6 Female 18-20 female 18 20 19
7 Female 18-20 female 18 20 20
叮當貓咪
TA貢獻1776條經驗 獲得超12個贊
這是使用新熊貓 0.25.0 的一種方法explode
s=dt['id_audience'].str.extractall('(\d+)')
dt['age']= [list(range(y.iloc[0,0],y.iloc[1,0]+1)) for x , y in s.astype(int).groupby(level=0)]
dt=dt.explode('age').reset_index(drop=True)
慕桂英4014372
TA貢獻1871條經驗 獲得超13個贊
使用Index.repeat和GroupBy.cumcount作為age列的計數器：
dt = dt.loc[dt.index.repeat(dt['age_max'] - dt['age_min'] + 1)]
dt['age'] = dt['age_min'] + dt.groupby(level=0).cumcount()
dt = dt.reset_index(drop=True)
print (dt)
id_audience gender age_min age_max age
0 Female 13-17 female 13 17 13
1 Female 13-17 female 13 17 14
2 Female 13-17 female 13 17 15
3 Female 13-17 female 13 17 16
4 Female 13-17 female 13 17 17
5 Female 18-20 female 18 20 18
6 Female 18-20 female 18 20 19
7 Female 18-20 female 18 20 20
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