Matplotlib 101 - Basic Introduction for Python Beginner

matplotlib-101-dataprep.py

# ---------- IMPORT PACKAGES ----------

# Dataframe manipulation
import pandas as pd

# Matrices operation
import numpy as np

# Data viz with matplotlib
import matplotlib
import matplotlib.pyplot as plt
from matplotlib import style

# Check packages' version
print('pandas     ', pd.__version__)
print('numpy      ', np.__version__)
print('matplotlib ', matplotlib.__version__)
print('seaborn    ', sns.__version__)

# ---------- LOAD DATA SET ----------

# Load the data set into Python
df = pd.read_csv(filepath_or_buffer = 'data/WA_Fn-UseC_-Telco-Customer-Churn.csv', sep = ';')

# Print top 5 rows
df.head(n = 5)

# Metadata
df.info()

# Change column types
df = df.astype({'SeniorCitizen': object})

# ---------- DATA PREPARATION ----------

# Number of missing values in a data frame
df.isnull().sum()

# Summary statistics
df.describe()

# Check the unique values of categorical columns
for col in df.select_dtypes('object').columns:
    print(df[str(col)].value_counts(), '\n')

# Data aggregation
df_group_1 = df.groupby('PaymentMethod')[['customerID']].count().reset_index()