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pythonpandasreplacemultiple-value

python replace multiple values from all columns in dataframe pandas

Below is a sample of my table.

DataFrame

Below is the code for the table:

d = {'1978': ['10k', '20000'],
    '1979': ['30k', '2M'],
    '1980': ['60000', '20k'],
    '1981': ['10000', '1M'],
    '1982': ['15000', '70k'],
    '1983': ['12k', '8M']}
df = pd.DataFrame(data=d)

Actually, the one I am working has 60 columns and 200 rows. However, It's the same structure.

My goal is to replace "k" for "000" and "M" for "000000" for all the rows of the many columns.

So the output should be:

Expected DataFrame

If someone could share with me the code to get this desired output, I would really appreciate.

Solution

  • You can use pandas.DataFrame.replace with a dictionary as argument and regex=True:

    new_df = df.replace({'k':'000', "M": "000000"}, regex=True)