我嘗試將多個新的dataFrames合并到一個主框架中。假設主數據框： key1 key20 0.365803 0.2591121 0.086869 0.5898342 0.269619 0.1836443 0.755826 0.0451874 0.204009 0.669371我嘗試將以下兩個數據集合并到主要數據集“新數據1 ”中： key1 key2 new feature0 0.365803 0.259112 info1新數據2： key1 key2 new feature0 0.204009 0.669371 info2預期結果： key1 key2 new feature0 0.365803 0.259112 info11 0.776945 0.780978 NaN2 0.275891 0.114998 NaN3 0.667057 0.373029 NaN4 0.204009 0.669371 info2我試過的test = test.merge(data1, left_on=['key1', 'key2'], right_on=['key1', 'key2'], how='left')test = test.merge(data2, left_on=['key1', 'key2'], right_on=['key1', 'key2'], how='left')第一個效果很好，但第二個效果不好，我得到的結果是： key1 key2 new feature_x new feature_y0 0.365803 0.259112 info1 NaN1 0.776945 0.780978 NaN NaN2 0.275891 0.114998 NaN NaN3 0.667057 0.373029 NaN NaN4 0.204009 0.669371 NaN info2謝謝你的幫助！
3 回答
aluckdog
TA貢獻1847條經驗 獲得超7個贊
首先append或concat兩者DataFrame在一起，然后merge：
dat = pd.concat([data1, data2], ignore_index=True)
或者：
dat = data1.append(data2, ignore_index=True)
print (dat)
key1 key2 new feature
0 0.365803 0.259112 info1
1 0.204009 0.669371 info2
#if same joined columns names better is only on parameter
df = test.merge(dat, on=['key1', 'key2'], how='left')
print (df)
key1 key2 new feature
0 0.365803 0.259112 info1
1 0.086869 0.589834 NaN
2 0.269619 0.183644 NaN
3 0.755826 0.045187 NaN
4 0.204009 0.669371 info2
胡說叔叔
TA貢獻1804條經驗 獲得超8個贊
您可以pd.DataFrame.update改用：
# create new column and set index
res = test.assign(newfeature=None).set_index(['key1', 'key2'])
# update with new data sequentially
res.update(data1.set_index(['key1', 'key2']))
res.update(data2.set_index(['key1', 'key2']))
# reset index to recover columns
res = res.reset_index()
print(res)
key1 key2 newfeature
0 0.365803 0.259112 info1
1 0.086869 0.589834 None
2 0.269619 0.183644 None
3 0.755826 0.045187 None
4 0.204009 0.669371 info2
哈士奇WWW
TA貢獻1799條經驗 獲得超6個贊
您還可以將數據幀設置為相同的索引并使用簡單 loc
df = df.set_index(["key1", "key2"])
df2 = df2.set_index(["key1", "key2"])
然后
df.loc[:, "new_feature"] = df2['new_feature']
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