CODEWITHSUNDEEP
pythonpandasdataframepandas-loc
Henrique Krupck Secchi
Henrique Krupck Secchi

Reputation: 5

How to use loc from pandas?

I have this code to replace ages from numeric data to categorical data. I'm trying to do it that way, but it's not working. Can anybody help me?

for df in treino_teste:
    df.loc[df['Age'] <= 13, 'Age'] = 0,
    df.loc[(df['Age'] > 13) & (df['Age'] <= 18), 'Age'] = 1,
    df.loc[(df['Age'] > 18) & (df['Age'] <= 25), 'Age'] = 2,
    df.loc[(df['Age'] > 25) & (df['Age'] <= 35), 'Age'] = 3,
    df.loc[(df['Age'] > 35) & (df['Age'] <= 60), 'Age'] = 4,
    df.loc[df['Age'] > 60, 'Age'] = 5

Error:

Error image

Upvotes: 0

Views: 351

Answers (2)

LevB
LevB

Reputation: 953

You can use numpy.digitize()

bins = [0,13,18,25,35,60,100]
df['AgeC'] =numpy.digitize(df['Age'],bins)

Upvotes: 1

Rob Raymond
Rob Raymond

Reputation: 31166

  • there is capability for categorising continuous data
  • for purpose of example I've assign the bin to a new column. I could have assigned it back to Age
  • for ease of reading results I have sorted, this is not needed
df = pd.DataFrame({"Age":np.random.randint(1,65,10)}).sort_values(["Age"])

bins = [0,13,18,25,35,60,100]
df.assign(AgeB=pd.cut(df.Age, bins=bins, labels=[i for i,v in enumerate(bins[:-1])]))
Age AgeB
5 12 0
3 13 0
8 18 1
7 25 2
9 25 2
1 27 3
2 30 3
4 57 4
0 59 4
6 64 5

Upvotes: 1

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