Data analysis and preprocessing using pandas

In this section, we will utilize pandas to do some analysis and preprocessing of the data before submitting it as input to scikit-learn.

Examining the data

To start our preprocessing of the data, let's read in the training dataset and examine what it looks like.

Here, we read the training dataset into a pandas DataFrame and display the first rows:

In [2]: import pandas as pd
        import numpy as np
# For .read_csv, always use header=0 when you know row 0 is the header row
       train_df = pd.read_csv('csv/train.csv', header=0)
In [3]: train_df.head(3)

The output is as follows:

Hence, we can see the various features...