Pandas: Incrementing values in a column based on condition

user_1571934 0
Viewed 1786

I have the following dataframe, and I would like to increment 'value' for all of the rows where value is between 2 and 7.

import pandas as pd
df = pd.DataFrame({"value": range(1,11)})
df

# Output
    value
0   1
1   2
2   3
3   4
4   5
5   6
6   7
7   8
8   9
9   10

I have tried two ways to do this, the first attempt failed with an error. The second attempt works but it is not the nicest solution. Can anyone provide a nicer solution?

# Attempt #1
df.loc[2 < df['value'] < 7, 'value'] += 1

# Ouput
ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().

# Attempt #2
def increment(value):
    if value > 2 and value < 7:
        return value + 1
    return value
df["value"] = df["value"].apply(lambda x : increment(x))

# Output
    value
0   1
1   2
2   4
3   5
4   6
5   7
6   7
7   8
8   9
9   10
pandas dataframe python
2 Answers

Try pandas.Series.between:

df.loc[df['value'].between(2,7, inclusive=False), 'value'] += 1

Output:

   value
0      1
1      2
2      4
3      5
4      6
5      7
6      7
7      8
8      9
9     10
user_42384080

You can do it this way:

df[(2 < df.value) & (df.value < 7)] += 1

or equivalently:

df[(df.value.gt(2)) & (df.value.lt(7))] += 1

Output in both cases:

   value
0      1
1      2
2      4
3      5
4      6
5      7
6      7
7      8
8      9
9     10
user_137432330
Related