[FIXED] Sklearn changing string class label to int

Issue

I have a pandas dataframe and I'm trying to change the values in a given column which are represented by strings into integers. For instance:

df = index    fruit   quantity   price 
         0    apple          5    0.99
         1    apple          2    0.99
         2   orange          4    0.89
         4   banana          1    1.64
       ...
     10023     kiwi         10    0.92

I would like it to look at:

df = index    fruit   quantity   price 
         0        1          5    0.99
         1        1          2    0.99
         2        2          4    0.89
         4        3          1    1.64
       ...
     10023        5         10    0.92

I can do this using

df["fruit"] = df["fruit"].map({"apple": 1, "orange": 2,...})

which works if I have a small list to change, but I'm looking at a column with over 500 different labels. Is there any way of changing this from a string to a an int?

Solution

Use factorize and then convert to categorical if necessary:

df.fruit = pd.factorize(df.fruit)[0]
print (df)
   fruit  quantity  price
0      0         5   0.99
1      0         2   0.99
2      1         4   0.89
3      2         1   1.64
4      3        10   0.92

---

df.fruit = pd.Categorical(pd.factorize(df.fruit)[0])
print (df)
  fruit  quantity  price
0     0         5   0.99
1     0         2   0.99
2     1         4   0.89
3     2         1   1.64
4     3        10   0.92

print (df.dtypes)
fruit       category
quantity       int64
price        float64
dtype: object

Also if need count from 1:

df.fruit = pd.Categorical(pd.factorize(df.fruit)[0] + 1)
print (df)
  fruit  quantity  price
0     1         5   0.99
1     1         2   0.99
2     2         4   0.89
3     3         1   1.64
4     4        10   0.92

Answered By - jezrael