merge 2 uneven dataframes without overwriting values in python

To merge two uneven dataframes without overwriting values, we can use pandas' "merge" function with outer join. Outer join will include all rows from both dataframes, filling in any missing values with NaN. Here is an example code that demonstrates this:

main.py
import pandas as pd

# create sample dataframes with overlapping columns
df1 = pd.DataFrame({'A': [1, 2, 3], 'B': ['a', 'b', 'c']})
df2 = pd.DataFrame({'A': [1, 2, 4], 'C': [True, False, True]})

# merge dataframes with outer join
merged_df = pd.merge(df1, df2, on='A', how='outer')

# print merged dataframe
print(merged_df)
326 chars
12 lines

In this code, we first create two sample dataframes with overlapping column "A". We then merge these dataframes using "merge" function with "outer" join and "A" as the join key. This will result in a merged dataframe that includes all rows from both dataframes, filling in missing values with NaN. Finally, we print the merged dataframe.