subtract a constant from a column to create a new one

Question

I have a geodata frame. I have a column and I would like to create a new one subtracting one if that column is strictly greater than 0, otherwise, maintain the same value.

I have tried the following:

df['new_column'] = df.apply(lambda y: (df['old_column'].subtract(1)) if y['old_column'] > 0 else y['old_column'], axis=1)

It’s doing well at the time to differentiate when old_column is greater than 0, but at the moment to substract one, it’s doing something strange, it’s not substracting, it’s just given a series of numbers, 3-2 2-1 1 1-1, things like that. Why is it doing that?

Asked By: OgeiD

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Answer 1

Instead of apply you can use np.where which is faster for bigger dataframes and easier to read.

import numpy as np
import pandas as pd

df = pd.DataFrame({"old_column": [-3, -2, -1, 0, 1, 2, 3]})
df["new_column"] = np.where(df.old_column > 0, df.old_column-1, df.old_column)

df

   old_column  new_column
0          -3          -3
1          -2          -2
2          -1          -1
3           0           0
4           1           0
5           2           1
6           3           2

If this does not work for your df, please include an example

Answered By: bitflip

Answer 2

The error is that you need to take one cell and not the entire column df[‘old_column’] => y[‘old_column’]. In addition, there is no subtract method for a numpy object.

df['new_column'] = df.apply(lambda y: (y['old_column'] - 1) if y['old_column'] > 0 else y['old_column'], axis=1)

A simpler expression if data from one column is used

df['new_column'] = df['old_column'].apply(lambda y: y - 1 if y > 0 else y)

Answered By: Victor Linde

subtract a constant from a column to create a new one

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