In [1]:

```
## How to Normalise a Pandas DataFrame Column
def Kickstarter_Example_96():
print()
print(format('How to Normalise a Pandas DataFrame Column','*^82'))
import warnings
warnings.filterwarnings("ignore")
# load libraries
import pandas as pd
from sklearn import preprocessing
# Create an example dataframe with a column of unnormalized data
data = {'score': [234,24,14,27,-74,46,73,-18,59,160]}
df = pd.DataFrame(data)
print(); print(df)
# Normalize The Column
# Create x, where x the 'scores' column's values as floats
x = df[['score']].values.astype(float)
print(); print(x)
# Create a minimum and maximum processor object
min_max_scaler = preprocessing.MinMaxScaler()
# Create an object to transform the data to fit minmax processor
x_scaled = min_max_scaler.fit_transform(x)
# Run the normalizer on the dataframe
df_normalized = pd.DataFrame(x_scaled)
# View the dataframe
print(); print(df_normalized)
Kickstarter_Example_96()
```

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