import pandas as pd import numpy as np import matplotlib.pyplot as plt import seaborn as sns

df = pd.read_csv('/work/largest_us_retailers.csv') df

average = round(df['Sales'][1:].mean(), 2) print(f'The average of sales is: {average} millions dollars') df = df.sort_values('Sales', ascending=0) plt.subplots(figsize=(6,8)) xaver = [df['Company'][0], 'Average of sales of other companies'] yaver = [df['Sales'][0], average] plt.bar(xaver,yaver) plt.title('Average of sales', fontsize='25', fontweight='bold') plt.ylabel('Millions of dollars', fontweight='bold') plt.show

plt.subplots(figsize=(6,10)) df = df.sort_values('Sales', ascending=0) sns.barplot(x=df['Sales'], y = df['Company']) #sns.despine(left=True, bottom=True) plt.title('Money generated by company', fontsize='25', fontweight='bold') plt.xlabel('Sales', fontweight='bold') plt.ylabel('Companies', fontweight='bold')

physical = df[(df['Stores'] > 0)] df = df.sort_values('Stores', ascending=0) plt.subplots(figsize=(6,10)) sns.barplot(x = physical['Stores'], y = df['Company']) plt.title('Number of stores by company', fontsize='25',fontweight='bold') plt.xlabel('number of stores', fontweight='bold') plt.ylabel('Companies', fontweight='bold')

ax, g = plt.subplots(figsize=(20,9)) physical = physical.sort_values('Stores', ascending=0) sns.set_theme(style='whitegrid') sns.barplot(data = physical, x = 'Sales', y = 'Company', label='Sales', color='b') sns.barplot(data = physical, x = 'Stores', y = 'Company', label ='Number of stores', color='red') plt.xlabel('Sales', fontweight='bold') plt.ylabel('Companies', fontweight='bold') plt.title('Sales vs number of stores', fontweight='bold', fontsize='25') ax.legend(ncol=2, loc='upper center', frameon =True)

sns.boxplot(data=df, x='Sales', width=0.5, fliersize=10) sns.despine(offset=20, trim=True) plt.title('Range of sales', fontsize='25',fontweight='bold') plt.xlabel('Sales', fontweight='bold')

plt.subplots(figsize=(12,7)) physical = physical.sort_values('Stores', ascending=0) sns.barplot(data=physical, x='Stores', y=physical['Company'][:5], palette='viridis') plt.title('Top 5 companies that have more stores', fontsize='25',fontweight='bold') plt.xlabel('Number of stores', fontweight='bold') plt.ylabel('Companies', fontweight='bold')

categories = df.groupby('Category').sum() plt.subplots(figsize=(8,8)) sns.scatterplot(data=categories, x='Sales', y='Category', size='Sales', hue='Category', sizes=(100, 5000), legend=False) plt.xlabel('Sales', fontweight='bold') plt.ylabel('Categories of stores', fontweight='bold') plt.title('Sales by categories', fontsize='25', fontweight='bold')

plt.subplots(figsize=(6,10)) df = df.sort_values('Sales', ascending=0) sns.barplot(x=df['Sales'], y = df['Company'][:15]) plt.ylabel('Company', fontweight='bold') plt.xlabel('Sales', fontweight='bold') plt.title('Sales', fontweight='bold', fontsize='25')