I want to change every value in a pandas data frame column-CodePudding

So I have this pandas data frame including a column for months it's type is int64, I want to change every value in the column to be the corresponding season of the year.

for example if x = 12,1,2 change the value of x to 'winter' etc.

I have tried some for loops but no use, I think there is a one liner that can do this using lambda x.

any ideas ?

CodePudding user response：

suppose you have this dataframe (named df)

then u can easily write this function

def map_fn(x: int):
    if x in range(3, 6):
        return "spring"
    if x in range(6, 9):
        return "summer"
    if x in range(9, 12):
        return "autumn"
    return "winter"

and then apply it to your column like this

df.seasons.apply(map_fn)

to have this

CodePudding user response：

map accepts a dict or a Series (values that are not found in the dict are converted to NaN).

https://pandas.pydata.org/docs/reference/api/pandas.Series.map.html

month2season = {1:'winter',2:'winter',3:'spring',...}
s.map(month2season)  # s.apply(month2season) does the same thing

CodePudding user response：

One fast and flexible way is to map a dict from current column values to new column values:

d = dict(zip(range(1,13), ["winter"]*2   ["spring"]*3   ["summer"]*3   ["fall"]*3   ["winter"]))    
df = pd.DataFrame(dict(month=[3,4,6,1,5,6,2,4,5]))

df = df.month.map(d)

output:

0    spring
1    spring
2    summer
3    winter
4    spring
5    summer
6    winter
7    spring
8    spring
Name: month, dtype: object