在 Python Pandas 中合并两个数据集
[英]Merge two data-sets in Python Pandas
问题描述
I have two datasets in the below format & want to merge them into a single dataset based on City+Age+Gender.
我有以下格式的两个数据集，并希望将它们合并为一个基于 City+Age+Gender 的数据集。 Thanks in advance提前致谢
Dataset1: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
Dataset2: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
Expected resulting dataset: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
Note : Feeds/Count signify the same meaning.注意：Feeds/Count 表示相同的含义。 So okay to have either of them as the column name in the merged dataset.所以可以将它们中的任何一个作为合并数据集中的列名。
1 个解决方案
解决方案1
1 已采纳 2017-10-31 08:01:49
Use pandas.concat with rename columns for align columns - need same columns in both DataFrames :使用带有rename列的pandas.concat来对齐列 - 在both DataFrames需要相同的列：
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
Alternative with DataFrame.append - not pure python append :替代DataFrame.append - 不是纯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
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