<jupyter_start><jupyter_text>Super Store EDA<jupyter_code>import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
df = pd.read_csv('data.csv')
df['Amount'] = df['Amount'].str.replace('$','').str.replace(',','')
df['Amount'] = pd.to_numeric(df['Amount'])
print(df.head())
# Remove unwanted 
df.drop('BranchName',axis=1, inplace=True)
df.head()
df.shape
df.describe()<jupyter_output><empty_output><jupyter_text>Distribution Plot<jupyter_code>num_bins = 10
plt.hist(df['Amount'], num_bins, normed=1, facecolor='blue', alpha=0.7)
plt.show()<jupyter_output><empty_output><jupyter_text>The data varies from `-1000` to `1000` sums up how much the amount varies.  Sales by Month, Day and Hour<jupyter_code># By Month
sales_by_month = df.groupby('Month').size()
print(sales_by_month)
#Plotting the Graph
plot_by_month = sales_by_month.plot(title='Monthly Sales',xticks=(1,2,3,4,5,6,7,8,9,10,11,12))
plot_by_month.set_xlabel('Months')
plot_by_month.set_ylabel('Total Sales')
# By Day
sales_by_day = df.groupby('Day').size()
plot_by_day = sales_by_day.plot(title='Daily Sales',xticks=(range(1,31)),rot=55)
plot_by_day.set_xlabel('Day')
plot_by_day.set_ylabel('Total Sales')<jupyter_output><empty_output><jupyter_text>As per this, 18th day was the best day as 151 units were sold in that day and sales drastically dropped by the end of the month. May be members get tired or bored? :-)<jupyter_code>sales_by_hour = df.groupby('Hour').size()
plot_by_hour = sales_by_hour.plot(title='Hourly Sales',xticks=(range(5,22)))
plot_by_hour.set_xlabel('Working Hours')
plot_by_hour.set_ylabel('Total Sales')<jupyter_output><empty_output>
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