Pandas Dataframe: Replace values in a column based on certain Range in values of the same column

Question

I have a simple DataFrame like the following:

lead	Rating
Clint	2
Saoro	1
Clint	3
Saoro	4
Clint	5
Clint	6
billy	9
Clint	10

I want to Replace rating column values as 1-3 - low, 4-6 - average, 7-8 - Good, 9-10 - Excellent

I tried with,

    df['Rating'].mask(df['Rating'] <=3 ,'low', inplace=True)
    df3['Rating'].mask((df3['Rating'] >=4) | (df3['Rating'] < 7) ,'average', inplace=True)

but this will give error " TypeError: '>=' not supported between instances of 'str' and 'int'" as it is taking into consideration the firstly replaced column value "low" also in the second line. Its the same when I tried using lamba function also.

Please check as Image is not available. Please reattach the image. Also, try to change data type of column Rating from String to Integer and It should work. use "astype" method of dataframe to do so. — Piyuushh Sambhi
– Piyuushh Sambhi, Commented Jul 28, 2022 at 8:22

Timus · Accepted Answer · 2022-07-28 08:58:23Z

4

In case the values in column Rating are strings: df["Rating"] = df["Rating"].astype("int")

First option - .replace() with a mapping dictionary:

mapping = {
    1: 'low', 2: 'low', 3: 'low',
    4: 'average', 5: 'average', 6: 'average',
    7: 'good', 8: 'good',
    9: 'excellent', 10: 'excellent'
}
df["Rating"] = df["Rating"].replace(mapping)

Second option - .map() with a mapping function:

def mapping(rating):
    if rating <= 3:
        return "low"
    if rating <= 6:
        return "average"
    if rating <= 8:
        return "good"
    return "excellent"

df["Rating"] = df["Rating"].map(mapping)

answered Jul 28, 2022 at 8:58

Timus

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