count_descriptive_statistics.py

# import the 
import pandas as pd
from matplotlib import cm
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.patches as patches
import matplotlib.path as path
import matplotlib.ticker as ticker
import matplotlib.animation as animation
import pandas as pd
from mpl_toolkits.axes_grid1 import make_axes_locatable

# Get numerical and categorical columns
total_columns = train.columns
num_col = train._get_numeric_data().columns
cat_col = list(set(total_columns)-set(num_col))

# find categorical columns category and their counts
for i in cat_col:
    print(i)
    print(train[i].value_counts())
   
# Plot graph for Item_Type category
index = np.arange(6)
fig, ax = plt.subplots(figsize=(15, 8))

list1x = list(dict(train['Item_Type'].value_counts()).keys())
list1y = list(train['Item_Type'].value_counts())
ax.barh(list1x, list1y, alpha=0.7,
         # width = 0.5,
        color=cm.Blues([i / 0.00525 for i in [ 0.00208, 0.00235, 0.00281, 0.00317, 0.00362, 0.00371, 0.00525, 0.00679, 0.00761, 0.00833]])
        )

plt.rcParams.update({'font.size': 10})
rects = ax.patches
for i, label in enumerate(list1y):
    ax.text(label , i, str(label), size=10, ha='left', va='center')

ax.text(0, 1.02, 'Item_Type Food Category Count', transform=ax.transAxes, size=12, weight=600, color='#777777')
ax.xaxis.set_ticks_position('bottom')
ax.tick_params(axis='x', colors='black', labelsize=9)
ax.set_axisbelow(True)
ax.text(0, -0.1, 'Source: https://datahack.analyticsvidhya.com/contest/practice-problem-big-mart-sales-iii/#ProblemStatement',
        transform=ax.transAxes, size=12, weight=600, color='#777777')
ax.spines['right'].set_visible(False)
ax.spines['top'].set_visible(False)
plt.show()