我有两个以下格式的数据集，希望根据城市+年龄+性别将它们合并为一个数据集。提前致谢
数据集1:
City Age Gender Source Count
0 California 15-24 Female Amazon Prime Video 14629
1 California 15-24 Female Fubo TV 3840
2 California 15-24 Female Hulu 54067
3 California 15-24 Female Netflix 11713
4 California 15-24 Female Sling TV 10642
数据集2:
City Age Gender Source Feeds
0 California 15-24 Female Blogs 150
1 California 15-24 Female Customsite 57
2 California 15-24 Female Discussions 28
3 California 15-24 Female Facebook Comment 555
4 California 15-24 Female Google+ 19
预期结果数据集:
City Age Gender Source Count
California 15-24 Female Amazon Prime Video 14629
California 15-24 Female Fubo TV 3840
California 15-24 Female Hulu 54067
California 15-24 Female Netflix 11713
California 15-24 Female Sling TV 10642
California 15-24 Female Blogs 150
California 15-24 Female Customsite 57
California 15-24 Female Discussions 28
California 15-24 Female Facebook Comment 555
California 15-24 Female Google+ 19
注:Feeds/Count 含义相同。因此可以将它们中的任何一个作为合并数据集中的列名称。
最佳答案
使用pandas.concat使用重命名列来对齐列 - 需要在两个DataFrames中使用相同的列:
df = pd.concat([df1, df2.rename(columns={'Feeds':'Count'})], ignore_index=True)
print (df)
City Age Gender Source Count
0 California 15-24 Female Amazon Prime Video 14629
1 California 15-24 Female Fubo TV 3840
2 California 15-24 Female Hulu 54067
3 California 15-24 Female Netflix 11713
4 California 15-24 Female Sling TV 10642
5 California 15-24 Female Blogs 150
6 California 15-24 Female Customsite 57
7 California 15-24 Female Discussions 28
8 California 15-24 Female Facebook Comment 555
9 California 15-24 Female Google+ 19
替代DataFrame.append - 不纯python append :
df = df1.append(df2.rename(columns={'Feeds':'Count'}), ignore_index=True)
print (df)
City Age Gender Source Count
0 California 15-24 Female Amazon Prime Video 14629
1 California 15-24 Female Fubo TV 3840
2 California 15-24 Female Hulu 54067
3 California 15-24 Female Netflix 11713
4 California 15-24 Female Sling TV 10642
5 California 15-24 Female Blogs 150
6 California 15-24 Female Customsite 57
7 California 15-24 Female Discussions 28
8 California 15-24 Female Facebook Comment 555
9 California 15-24 Female Google+ 19
关于python - 在 Python Pandas 中合并两个数据集，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/47030450/