Concatenate 2 dataframes and repeat values from small one with pandas-CodePudding

I have these two dataframes:

Field1	Field2
0.5	0.7
2	1
3	0.1
4	0.4

and

Date	Time
2022-08-01	1
2022-08-01	2

and a I need to obtain the following:

Field1	Field2	Date	Time
0.5	0.7	2022-08-01	1
2	1	2022-08-01	2
3	0.1	2022-08-01	1
4	0.4	2022-08-01	2

Thanks in advance

CodePudding user response：

You can elongate your second dataframe to match dimentions, and then concatenate it with first dataframe.

import pandas as pd

df1 = pd.DataFrame({'Field1': [0.5, 2, 3, 4], 'Field2': [0.7, 1, 0.1, 0.4]})
print(df1)
#    Field1  Field2
# 0     0.5     0.7
# 1     2.0     1.0
# 2     3.0     0.1
# 3     4.0     0.4

df2 = pd.DataFrame({'Date': ['2022-08-01', '2022-08-01'], 'Time': [1, 2]})
print(df2)
#          Date  Time
# 0  2022-08-01     1
# 1  2022-08-01     2

n = int(df1.size / df2.size)
df3 = pd.concat([df2] * n, axis=0).reset_index(drop=True)
print(df3)
#          Date  Time
# 0  2022-08-01     1
# 1  2022-08-01     2
# 2  2022-08-01     1
# 3  2022-08-01     2

df4 = pd.concat([df1, df3], axis=1)
print(df4)
#    Field1  Field2        Date  Time
# 0     0.5     0.7  2022-08-01     1
# 1     2.0     1.0  2022-08-01     2
# 2     3.0     0.1  2022-08-01     1
# 3     4.0     0.4  2022-08-01     2

or shorter:

df4 = pd.concat([
    df1,
    pd.concat(
        [df2] * int(df1.size / df2.size),
        axis=0
    ).reset_index(drop=True)
], axis=1)

CodePudding user response：

Here is a possible solution (df1 is your first dataframe, df2 is your second dataframe):

result = pd.concat(
    [df1,
     pd.concat(
         [df2] * (len(df1) // len(df2)   1),
         ignore_index=True,
     ).head(len(df1))
    ],
    axis=1,
)

Here is the result:

>>> result
   Field1  Field2        Date  Time
0     0.5     0.7  2022-08-01     1
1     2.0     1.0  2022-08-01     2
2     3.0     0.1  2022-08-01     1
3     4.0     0.4  2022-08-01     2