Calculate date using different columns of a dataframe

Question

I have a dataframe with columns like this. The final df should contain a new column after taking the First_Date column and subtracting the corresponding unit and the corresponding value df = pd.DataFrame({"First_Date":[pd.to_datetime("2020-01-01")]*5, "Unit":['Years','Months','Days','Years','Days'], "Value":[1,2,2,3,5]})

The output column should have the values: 2019-01-01 2019-11-01 2020-12-29 2017-01-01 2020-12-27

I have tried the timedelta module but the inputs to that is not accepting values from a different column. For example, it does not take

df.apply(lambda x: x['First_Date']- timedelta(x['Unit'] = x['Value'])

Lukas Thaler · Accepted Answer · 2020-08-31 12:32:34Z

1

Named arguments cannot be supplied from a variable as far as I am aware.

You could, however, create a one-hot encoding for your Unit-column and scale it by the Value-column to create a description of your delta:

df_augmented = df.merge(pd.get_dummies(df.Unit).mul(df.Value, axis=0),
                        left_index=True, right_index=True)

  First_Date    Unit  Value  Days  Months  Years
0 2020-01-01   Years      1     0       0      1
1 2020-01-01  Months      2     0       2      0
2 2020-01-01    Days      2     2       0      0
3 2020-01-01   Years      3     0       0      3
4 2020-01-01    Days      5     5       0      0

Now, you can statically supply all values to the function (as in years=df_augmented.Years, months=df_augmented.Months etc) and all should be well.

answered Aug 31, 2020 at 12:32

Lukas Thaler

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