Women In Tech
Women in Tech
This analysis uses the 2020 survey data from StackOverflow to get a glimpse into where women are in the tech world.
This project is the course project for the Data Analysis with Python: Zero to Pandas course.
This project is an extension to "Lesson 6 - Exploratory Data Analysis - A Case Study" of the course.
The course is a hands-on introductory to data analysis using Python programming language along with fundamental but essential library packages for data analysis and visualization.
The dataset contains responses from software development community on Stack Overflow (stackoverflow.com).
How to run the code
This is an executable Jupyter notebook hosted on Jovian.ml, a platform for sharing data science projects. You can run and experiment with the code in a couple of ways: using free online resources (recommended) or on your own computer.
Option 1: Running using free online resources (1-click, recommended)
The easiest way to start executing this notebook is to click the "Run" button at the top of this page, and select "Run on Binder". This will run the notebook on mybinder.org, a free online service for running Jupyter notebooks. You can also select "Run on Colab" or "Run on Kaggle".
Option 2: Running on your computer locally
Install Conda by following these instructions. Add Conda binaries to your system
PATH, so you can use the
condacommand on your terminal.
Create a Conda environment and install the required libraries by running these commands on the terminal:
conda create -n zerotopandas -y python=3.8 conda activate zerotopandas pip install jovian jupyter numpy pandas matplotlib seaborn opendatasets --upgrade
- Press the "Clone" button above to copy the command for downloading the notebook, and run it on the terminal. This will create a new directory and download the notebook. The command will look something like this:
jovian clone notebook-owner/notebook-id
- Enter the newly created directory using
cd directory-nameand start the Jupyter notebook.
You can now access Jupyter's web interface by clicking the link that shows up on the terminal or by visiting http://localhost:8888 on your browser. Click on the notebook file (it has a
.ipynb extension) to open it.
Downloading the Dataset
Use the jovian opendatasets library to retrieve the CSV file from stackoverflow.com
!pip install jovian opendatasets --upgrade --quiet
Let's begin by downloading the data, and listing the files within the dataset.