*** This Notebook is Under Construction *** There are no guarantees that this notebook works or has all the required dependencies in the repository.

Other tools for Data Analysis

As you have seen no doubt, all of the techniques are valuable to get a good understanding of our data. There is hardly a project explanation or walkthrough of using any of the modelling techniques which doesn’t first start with some kind of summary stats, a histogram and correlation matrix. So much so that there are dozens of Python libraries that have encapsulated the most common techniques and automated them for you.

Examples include: pandas_profiling, dtale, bamboolib, and sweetviz

# Import relevant libraries
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

import seaborn as sns
from pathlib import Path
import sys
sys.path.append('..')
from src.data import load_data

# you can find available styles with plt.style.available
plt.style.use('fivethirtyeight')
plt.rcParams["figure.figsize"] = (20, 10)

toyota_df = load_data("ToyotaCorolla")

from pandas_profiling import profile_report
toyota_df.profile_report()

from dataprep.eda import create_report
create_report(toyota_df)