StandardScaler: TypeError: fit() 缺少 1 个必需的位置参数：'X'

Question

I am using StandardScaler to scaling my dataframe like below, and I got an error of ypeError: fit() missing 1 required positional argument: 'X'. I am not sure where is the problem? Thanks for your help.

import seaborn as sns
import pandas as pd
from random import randrange
import random
import numpy as np
from sklearn.preprocessing import StandardScaler # for feature scaling

random.seed(10)

df = pd.DataFrame()
for i in range(0,50):
    df = df.append({'x': randrange(1,10),
                    'y': randrange(10,21),
                    'depth':randrange(400,601)}, ignore_index=True)
df.head()


depth   x   y
0   523.0   1.0 16.0
1   518.0   1.0 13.0
2   567.0   8.0 14.0
3   533.0   3.0 10.0
4   419.0   8.0 15.0

scaler = StandardScaler

scaler.fit(df)
df_scaled= scaler.transform(df)

The error is:

TypeError                                 Traceback (most recent call last)
<ipython-input-40-98ea46087b3f> in <module>
      4 scaler = StandardScaler
      5 
----> 6 scaler.fit(df)
      7 df_scaled= scaler.transform(df)

TypeError: fit() missing 1 required positional argument: 'X'

Answer 1

You have to write

scaler = StandardScaler() 

You forgot the parenthesis