GitHub

Description

Leveraging exploratory data analysis in Python to examine Instagram profiles and determine the one with the highest number of followers, among other insights.

Skills Applied: Python

Libraries Used: pandas, plotly, matplotlib

Implementation

  • To initiate the analysis, I will import the CSV dataset into Jupyter Notebook to facilitate the required analysis.
  • Following that, I will initiate an initial Exploratory Data Analysis (EDA) by inspecting the data types of variables (.dtypes) and generating descriptive statistics (.describe). This preliminary examination will offer valuable insights into the characteristics of the variables and aid in identifying any required modifications prior to further in-depth analysis.
  • Following that, I will conduct a detailed analysis by creating various charts (Plotly, Matplotlib) and performing in-depth data breakdowns, enabling a comprehensive exploration.

Breakdown

PYTHON

  • To ensure ease of access and a better understanding of the code and analysis, I have prepared a detailed breakdown of every aspect of my analysis.
  • It would be more convenient for you to download and review the code, along with the comprehensive analysis, using your preferred platform such as Visual Studio Code or Jupyter Notebook.
  • This will allow you to digest the information more effectively and make the most of the insights provided.

Click here to download the code + dataset.

OR

Click here to view it online

Overview of the analysis:

  • Importing Libraries and dataset
    • Pandas
    • Plotly
    • MatplotLib
  • Exploratory Data Analysis
    • Data Types
  • Statistics Summary
    • Min, Max, Mean, Count
    • Standard Deviation
  • Data Analysis
    • Histogram (MatplotLib version)
    • Histogram (Plotly version)
    • Bar Chart

Preview