TheSegunAdebiyi/linear-regression-Using-Python-

Analyzing and Predicting Adjusted Net National Income per Capita in Nigeria: A Python Data Science Journey # linear-regression-Using-Python Analyzing and Predicting Adjusted Net National Income per Capita in Nigeria: A Python Data Science Journey ### Project Overview In the realm of data science, understanding and predicting economic indicators play a pivotal role in decision-making processes. In this project, we delved into the intricacies of Nigeria's economic landscape by exploring the Adjusted Net National Income (ANNI) per capita. Employing Python, along with libraries such as pandas, seaborn, matplotlib, and sklearn, we embarked on a comprehensive analysis and prediction journey. ### Data Source World Bank staff estimates based on sources and methods in World Bank's "The Changing Wealth of Nations: Measuring Sustainable Development in the New Millennium" ( 2011 ). Download here ### Data Collection and Cleaning - We kickstarted the project by sourcing relevant data on Nigeria's Adjusted Net National Income per Capita. This involved gathering historical data to establish a robust foundation for our analysis. Leveraging pandas. - we meticulously cleaned the data by handling missing values, outliers, and ensuring data integrity. This step is crucial for accurate modeling and forecasting. ```python import pandas as pd # Read the CSV file into a DataFrame file_path = 'Adjusted net national income per capita (current US$) - Nigeria - Sheet1.csv' df = pd.read_csv(file_path) # Remove commas from the "Value" column and convert it to float df['Value'] = df['Value'].str.replace(',', '').astype(float) # Display the updated DataFrame df # Save the DataFrame to a CSV file df.to_csv('output_file.csv', index=False) ``` ### Exploratory Data Analysis (EDA) -Seaborn and matplotlib were employed to visualize the distribution of ANNI per capita over time. We created insightful visualizations, such as line plots and histograms, to uncover trends, patterns, and potential anomalies within the data. -Correlation matrices and heatmaps aided in identifying relationships between ANNI per …