How replace values of column with specific value in python?

Question

I am new to pandas, I am facing issue with replacing. So I am creating a function which replaces the values of column of a data frame based on the parameters. The condition is that it should replace all values of the column with only one value, as show below: Though I tried getting an error 'lenght didn't match'

    def replace(df,column,condition):
          for i in column:
              for j in condition:
                   df[i]=j
          return df
    column = ['A','C']
    condition = 11,34
    df
        A  B  C 
     0  12 5  1
     1  13 6  5
     2  14 7  7
    replace(df,column,condition)

my excepted output:

        A  B  C 
     0  11 5  34
     1  11 6  34
     2  11 7  34

rhurwitz · Accepted Answer · 2021-02-15 20:25:50Z

1

Edit: I initially sugggested using apply but then realized that is not necessary since you are ignoring the existing values in the series. This is simpler and should serve your purposes.

Example:

import pandas as pd

data = [[12, 5, 1], [13, 5, 5], [14, 7, 7]]
df = pd.DataFrame(data, columns = ["A", "B", "C"])

def replace(df, columns, values):
    for one_column, one_value in zip(columns, values):
        df[one_column] = one_value

    return df

print(replace(df, ["A", "C"], [11, 34]))

Output:

    A  B   C
0  11  5  34
1  11  5  34
2  11  7  34

edited Feb 15, 2021 at 20:25

answered Feb 15, 2021 at 20:15

rhurwitz

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2 Comments

sree Over a year ago

now what does .apply(lambda _:one_value) do?

rhurwitz Over a year ago

apply allows you to use the existing the contents of the series to compute new values. It is appropriate, for example, if you want to multiply each number in the series by 2. In your case, you don't care about the existing contents of the series, so apply is overkill.

wwnde · Accepted Answer · 2021-02-15 20:12:21Z

1

Using key:value pair, convert condition and column into a dict, unpack and assign the values

df.assign(**dict(zip(column, condition)))

answered Feb 15, 2021 at 20:12

wwnde

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