project-001:crm analysis

data cleaning

import pandas as pd

Load the Excel file

file_path = '' # Replace with your file path if youre running on a local ide, if online you upload your file at this point alphasports_data = pd.read_excel(file_path)

Setting the correct header and dropping unnecessary columns and rows

alphasports_data.columns = alphasports_data.iloc[1] # Set the second row as the header alphasports_data = alphasports_data.drop([0, 1]) # Drop the first two rows

Drop empty or irrelevant columns

alphasports_data = alphasports_data.dropna(axis=1, how='all')

Cleaning 'Slot Date' column

alphasports_data['Slot Date'] = alphasports_data['Slot Date'].apply(lambda x: x.strip() if isinstance(x, str) else x) alphasports_data['Slot Date'] = pd.to_datetime(alphasports_data['Slot Date'], errors='coerce')

Converting 'Slot Cost' to numeric

alphasports_data['Slot Cost'] = pd.to_numeric(alphasports_data['Slot Cost'], errors='coerce')

#analysis of time popularity, logic implementation

Analyzing the frequency of bookings for each time slot

slot_time_counts = alphasports_data['Slot time'].value_counts()

Sorting the results to see the most and least busy slots

sorted_slot_time_counts = slot_time_counts.sort_values(ascending=False)