Análisis de los 25 retailers más grandes de Estados Unidos

import pandas as pd import numpy as np import altair as alt

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

df.columns

alt.Chart(df).mark_bar(color = '#ffacd9').encode( x = alt.X('Sales', title = '', axis=alt.Axis(grid = False,labelFontSize=12,labels = False,ticks = False, domain = False)), y = alt.Y('Company', title = '',sort = '-x', axis=alt.Axis(grid = False,labelFontSize=14)), tooltip = [alt.Tooltip('Company',title = 'Company'),alt.Tooltip('Sales', title = 'Sales MUSD')] ).configure_title( fontSize = 18, anchor = 'middle', color = '#e4007c' ).configure_view( strokeWidth=0 ).properties ( title = 'Sales' )

# Quitar los datos de Walmart US para el cálculo del promedio companies = df[df['Company'] != 'Walmart US'] # Visualizar el cambio en una gráfica bar = alt.Chart(companies).mark_bar(color = '#ff79c2').encode( x = alt.X('Sales', title = '', axis=alt.Axis(grid = False,labelFontSize=12,labels = False,ticks = False, domain = False)), y = alt.Y('Company', title = '', sort = '-x', axis=alt.Axis(grid = False,labelFontSize=14)), tooltip = [alt.Tooltip('Company',title = 'Company'),alt.Tooltip('Sales', title = 'Sales MUSD')] ) m = alt.Chart(companies).mark_rule(color = 'black').encode( y = alt.Y('mean(Sales)',title = '',axis=alt.Axis(labels = False,ticks = False, domain = False)), tooltip = [alt.Tooltip('mean(Sales)', title = 'mean MUSD')] ) (bar + m).properties ( title = 'Sales' ).configure_title( fontSize = 18, anchor = 'middle', color = '#e4007c' ).configure_view( strokeWidth=0 )

meanCompanies = companies['Sales'].mean() meanCompanies

# Visualizar el cambio en una gráfica bar = alt.Chart(df).mark_bar(color = '#679997').encode( x = alt.X('Sales:Q',bin=alt.Bin(maxbins=60),title = 'Sales [M USD]'), y = alt.Y('count(Sales)', title = '',axis=alt.Axis(grid=False)) ) m = alt.Chart(df).mark_rule(color = 'black').encode( x = alt.X('mean(Sales)',title = '',axis=alt.Axis(ticks = False, domain = False)), tooltip = [alt.Tooltip('median(Sales)', title = 'median MUSD')] ) (bar + m).properties ( title = 'Sales' ).configure_title( fontSize = 18, anchor = 'middle', color = '#679997' ).configure_view( strokeWidth=0 )

medianSales = df['Sales'].median() medianSales

bar = alt.Chart(companies).mark_bar(color = '#9ae5e2').encode( x = alt.X('Sales:Q',bin=alt.Bin(maxbins=10),title = 'Sales [M USD]'), y = alt.Y('count(Sales)', title = '',axis=alt.Axis(grid=False)) ) m = alt.Chart(df).mark_rule(color = 'black').encode( x = alt.X('mean(Sales)',title = '',axis=alt.Axis(ticks = False, domain = False)), tooltip = [alt.Tooltip('median(Sales)', title = 'median (all data)')] ) (bar + m).properties ( title = 'Sales' ).configure_title( fontSize = 18, anchor = 'middle', color = '#679997' ).configure_view( strokeWidth=0 )

alt.Chart(df).mark_bar(color = 'skyblue').encode( x = alt.X('Stores:Q', title='Sales [M USD]',bin=alt.Bin(maxbins=10), axis=alt.Axis(domain = False)), y = alt.Y('count()', title='', axis=alt.Axis(grid=False, domain=False, ticks = False, )), tooltip = [alt.Tooltip('count()', title='Companies')] ).configure_view( strokeWidth=0 ).properties ( title = 'Sales' )

sel = pts = alt.selection(type = 'single') stores = alt.Chart(df).mark_bar().encode( x = alt.X('Sales', title = '', axis=alt.Axis(grid = False,labelFontSize=12,labels = False,ticks = False, domain = False)), y = alt.Y('Company', title = 'Sales', sort='-x', axis=alt.Axis(grid = False,labelFontSize=14,titleAnchor='start',titleAngle=0,titleFontSize=20, titleColor='#e4007c')), tooltip = [alt.Tooltip('Company',title = 'Company'),alt.Tooltip('Sales', title = 'Sales MUSD'),alt.Tooltip('Stores',title='Stores')], color = alt.condition(pts, alt.ColorValue("#ffacd9"), alt.ColorValue("grey")) ).add_selection(pts) sales = alt.Chart(df).mark_bar(color = 'skyblue').encode( x = alt.X('Stores', title = '', axis=alt.Axis(grid = False,labelFontSize=12,labels = False,ticks = False, domain = False)), y = alt.Y('Company', title = 'Stores', sort='-x', axis=alt.Axis(grid = False,labelFontSize=14,titleAnchor='start',titleAngle=0,titleFontSize=20, titleColor='steelblue')), tooltip = [alt.Tooltip('Company',title = 'Company'),alt.Tooltip('Sales', title = 'Sales MUSD'),alt.Tooltip('Stores',title='Stores')], color = alt.condition(pts, alt.ColorValue("skyblue"), alt.ColorValue("grey")) ).add_selection(pts) (stores | sales ).configure_view( strokeWidth=0 )

alt.Chart(df).mark_boxplot().encode( y = alt.Y('Sales') ) | alt.Chart(companies).mark_boxplot().encode( y = alt.Y('Sales') ).interactive()

rango = df['Sales'].max() - df['Sales'].min() rango

top = df.sort_values('Stores', ascending=False) top5Stores = top.iloc[:5] top5Stores

sales = alt.Chart(df).mark_bar().encode( x = alt.X('Stores', title = '', axis=alt.Axis(grid = False,labelFontSize=12,labels = False,ticks = False, domain = False)), y = alt.Y('Company', title = 'Stores', sort='-x', axis=alt.Axis(grid = False,labelFontSize=14, titleAnchor='start',titleAngle=0,titleFontSize=18)), tooltip = [alt.Tooltip('Company',title = 'Company'),alt.Tooltip('Sales', title = 'Sales MUSD'),alt.Tooltip('Stores',title='Stores')], color = alt.condition( alt.datum.Stores >= 4574, alt.ColorValue("orange"), alt.ColorValue("steelblue")) ) stores = alt.Chart(top5Sales).mark_bar().encode( x = alt.X('Sales', title = '', axis=alt.Axis(grid = False,labelFontSize=12,labels = False,ticks = False, domain = False)), y = alt.Y('Company', title = 'Top 5: Sales', sort='-x', axis=alt.Axis(grid = False,labelFontSize=14,titleAnchor='start',titleAngle=0,titleFontSize=18)), tooltip = [alt.Tooltip('Company',title = 'Company'),alt.Tooltip('Sales', title = 'Sales MUSD'),alt.Tooltip('Stores',title='Stores')], color = alt.condition( alt.datum.Stores >= 4574, alt.ColorValue("orange"), alt.ColorValue("steelblue")) ) ( sales | stores ).configure_view( strokeWidth=0 )

alt.Chart(df).mark_bar( color="lightblue" ).encode( x = alt.X('Sales', title='', axis=alt.Axis(grid=False, format='.2s',labels = False,ticks = False, domain = False)), y = alt.Y('Category', title=''), tooltip = [alt.Tooltip('Sales', title='Sales [M USD]')] ).configure_view( strokeWidth=0 ).properties( title = 'Sales per Category' ).configure_title( fontSize = 18, anchor = 'middle', color = 'steelblue' )

alt.Chart(df).mark_bar(color='orange').encode( x= alt.X('Sales\/Avg\. Store:Q', title = '', axis=alt.Axis(grid=False)), y= alt.Y('Company', title=''), tooltip = 'Sales\/Avg\. Store:Q' ).configure_view( strokeWidth=0 ).properties( title = 'Average sales per Store' )

df[np.isnan(df['Stores'])]

alt.Chart(df).mark_bar().encode( x = alt.X('Sales', title = '', axis=alt.Axis(grid = False,labelFontSize=12,labels = False,ticks = False, domain = False)), y = alt.Y('Company', title = 'Stores', sort='-x', axis=alt.Axis(grid = False,labelFontSize=14, titleAnchor='start',titleAngle=0,titleFontSize=18)), tooltip = [alt.Tooltip('Company',title = 'Company'),alt.Tooltip('Sales', title = 'Sales MUSD'),alt.Tooltip('Stores',title='Stores')], color = alt.condition( alt.datum.Stores, alt.ColorValue("steelblue"), alt.ColorValue("orange")) )