Ojayy94/Exploratory-Data-Analysis-With-Python

Exploratory Data Analysis - Axia Africa # Exploratory Data Analysis With Python ## Objectives: The purpose of this test is to assess your ability to handle data analysis tasks using Python. You will be working with a fictional dataset and will be expected to: - Perform data cleaning to handle missing or incorrect values. - Conduct feature engineering to create new insights from existing data. - Utilize data visualization techniques to explore and present data. - Analyze the dataset to extract meaningful patterns and insights. - Apply various data analysis techniques to answer specific questions related to the dataset. ## Instructions: ### Data Cleaning: **Task**: Identify and handle missing values in the 'Sales' and 'Cost' columns. Replace missing values with the mean of their respective columns. **Question**: What is the total number of missing values in the dataset before cleaning? ### Feature Engineering: **Task**: Create a new column named 'Profit/Loss' that calculates the difference between 'Sales' and 'Cost'. **Question**: After creating the 'Profit/Loss' column, what is the average 'Profit/Loss' for product 'A'? ### Data Visualization: **Task**: Create a bar chart showing the total 'Sales' for each product across all regions. **Question**: Which product has the highest total sales? ### Profit Analysis: **Task**: Analyze the 'Profit/Loss' column to determine the most profitable product. **Question**: Which product has the highest average 'Profit/Loss' across all regions? ### Time Series Analysis: **Task**: Plot the sales trends over time for all products. **Question**: Identify any observable trends or seasonality in the sales data. ### Correlation Analysis: **Task**: Calculate the correlation between 'Sales', 'Cost', and 'Profit/Loss'. **Question**: Which pair of variables has the highest correlation? ### Filtering and Aggregation: **Task**: Filter the dataset for sales in the 'North' region and calculate the total profit for this region. **Question**: What is the total profi …