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How to concat columns of similar dataframes with new names

Time:02-23

I have two dataframes with similar columns:

df1 = (a, b, c, d)
df2 = (a, b, c, d)

I want concat or merge some columns of them like below in df3

   df3 = (a_1, a_2, b_1, b_2)

How can I put them beside as they are (without any change), and how can I merge them on a similar key like d? I tried to add them to a list and concat them but don't know how to give them a new name. I don't want multi-level column names.

   for ii, tdf in enumerate(mydfs):
       tdf = tdf.sort_values(by="fid", ascending=False)
        for _col in ["fid", "pred_text1"]:
            new_col = _col   str(ii)
            dfs.append(tdf[_col])
        ii  = 1
    df = pd.concat(dfs, axis=1)

CodePudding user response:

Without having a look at your dataframe, it would not be easy, but I am generating a dataframe to give you samples and insight into how the code works:

import pandas as pd
import re
df1 = pd.DataFrame({"a":[1,2,4], "b":[2,4,5], "c":[5,6,7], "d":[1,2,3]})
df2 = pd.DataFrame({"a":[6,7,5], "b":[3,4,8], "c":[6,3,9], "d":[1,2,3]})
mergedDf = df1.merge(df2, how="left", on="d").rename(columns=lambda x: re.sub("(. )\_x", r"\1_1", x)).rename(columns=lambda x: re.sub("(. )\_y", r"\1_2", x))
mergedDf

which results in:

a_1 b_1 c_1 d a_2 b_2 c_2
0 1 2 5 1 6 3 6
1 2 4 6 2 7 4 3
2 4 5 7 3 5 8 9

If you are interested in dropping other columns you can use code below:

mergedDf.iloc[:, ~mergedDf.columns.str.startswith("c")]

which results in:

a_1 b_1 d a_2 b_2
0 1 2 1 6 3
1 2 4 2 7 4
2 4 5 3 5 8
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