我尝试将多个新数据帧合并到一个主数据帧中。 假设主数据框:
key1 key2
0 0.365803 0.259112
1 0.086869 0.589834
2 0.269619 0.183644
3 0.755826 0.045187
4 0.204009 0.669371
我尝试将以下 2 个数据集合并到主数据集中,
新数据1:
key1 key2 new feature
0 0.365803 0.259112 info1
新数据2:
key1 key2 new feature
0 0.204009 0.669371 info2
预期结果:
key1 key2 new feature
0 0.365803 0.259112 info1
1 0.776945 0.780978 NaN
2 0.275891 0.114998 NaN
3 0.667057 0.373029 NaN
4 0.204009 0.669371 info2
我尝试过的:
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')
对于第一个效果很好,但对于第二个效果不佳,我得到的结果:
key1 key2 new feature_x new feature_y
0 0.365803 0.259112 info1 NaN
1 0.776945 0.780978 NaN NaN
2 0.275891 0.114998 NaN NaN
3 0.667057 0.373029 NaN NaN
4 0.204009 0.669371 NaN info2
感谢您的帮助!
最佳答案
第一append
或concat
两个DataFrame
在一起,然后合并
:
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
关于python - 合并多个数据框pandas,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/51115262/