Python Pandas：合并两个数据框时控制新列名？
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Pandas: control new column names when merging two dataframes?
提问by Richard
I would like to merge two Pandas dataframes together and control the names of the new column values.
我想将两个 Pandas 数据框合并在一起并控制新列值的名称。
I originally created the dataframes from CSV files. The original CSV files looked like this:
我最初是从 CSV 文件创建数据框的。原始 CSV 文件如下所示：
# presents.csv
org,name,items,spend...
12A,Clerkenwell,151,435,...
12B,Liverpool Street,37,212,...
...
# trees.csv
org,name,items,spend...
12A,Clerkenwell,0,0,...
12B,Liverpool Street,2,92,...
...
Now I have two data frames:
现在我有两个数据框：
df_presents = pd.read_csv(StringIO(presents_txt))
df_trees = pd.read_csv(StringIO(trees_txt))
I want to merge them together to get a final data frame, joining on the organd namevalues, and then prefixing all other columns with an appropriate prefix.
我想将它们合并在一起以获得最终的数据框，加入org和name值，然后使用适当的前缀为所有其他列添加前缀。
org,name,presents_items,presents_spend,trees_items,trees_spend...
12A,Clerkenwell,151,435,0,0,...
12B,Liverpool Street,37,212,2,92,...
I've been reading the documentation on merging and joining. This seems to merge correctly and result in the right number of columns:
我一直在阅读有关合并和加入的文档。这似乎正确合并并导致正确的列数：
ad = pd.DataFrame.merge(df_presents, df_trees,
on=['practice', 'name'],
how='outer')
But then doing print list(aggregate_data.columns.values)shows me the following columns:
但后来做print list(aggregate_data.columns.values)向我展示了以下列：
[org', u'name', u'spend_x', u'spend_y', u'items_x', u'items_y'...]
How can I rename spend_xto be presents_spend, etc?
我怎样才能重命名spend_x为presents_spend，等等？
采纳答案by itzy
回答by Nguyen Ngoc Tuan
You can rename all the columns of adby setting its columnsas follows.
您可以重命名的所有列广告设置其列如下。
ad.columns = ['org', 'name', 'presents_spend', 'trees_spend']
回答by Amirkhm
Another way is adding suffix to the columns of your dataframe before merging:
另一种方法是在合并之前向数据框的列添加后缀：
ad.columns = 'ad_' + ad.columns.values
