final_​project112

Cafe_sales file

Calculated revenue from the quantity and price per unit sold

To know the numerical statistics of the data along with the 10 most common values

To count the occurence of all the unique values in the item colum

To know the correlation between two variables, here I have selected price per quantity and item column

To know the numerical statistics of the data from the cafe_sales file

Statistical view of the numerical data after data transformation and cleaning

To show the relationship between revenue and items variables

Pie chart depicting items with their revenue

For the analysis of different items and their quantities , revenue and price per unit

To know whether there is a normal curve or not for the quantity column

To show the relationship between two variables, here I have selected Item and Price per unit sold

To know the Q1, Q2, AND Q3 along with Iqr of the numerical data

To the Q1, Q2 and Q3 of the data along with IQR and min and max values

Converted the Quantity and Price per unit column which where in the string format to the number (float ) format

Converted the Transaction date column which was in string format to the date format

Filtering out all the duplicate rows

Handling all the missing values in different columns and replacing them with the most frequent value to avoid the effects of the outliers

Created a new column High/Mid demand products if the quantity of the items sold is more than 4 and 3

Removed the old Payment method column which inconsistencies

Converted all the strings in the payment method to capitalize format to remove inconsistencies

Grouped Item and revenue columns for further analysis