Once you have decided that Python is your language of choice for your data Analysis/Science project, download Python from its website. You can use the Integreted Development Learning Environment (IDLE) that comes with python but for easier learning experience, you can choose another IDE of your choice with a simple google search. Once your python is ready, you can pip install the library you want to use and start your data analysis project.
Python libraries are code modules that are used in solving python problems. Depending on the project, there are a number of libraries in Python for Data Analysts and Scientists alike. These include: Pandas, Numpy, Matplotlib, Seaborn, Plotly, Altair, Scikit-learn, etc.
1 Visit the website of your library of choice to get familiar with its documentation.
2 Pip install the library on your Personal computer (PC).
3 Study how to use the library from from its website, google search, youtube video, chatgpt, deepseek and walaaaa! You can start solving problems.
Python Pandas is used for analysing structured or tabular data (data stored in rows and columns) popularly called dataframe. You can learn more about Pandas from its website.
# Install Pandas
pip install pandas # for most IDEs
conda install -c conda-forge pandas #for Anaconda or miniconda First, import Pandas.
import Pandas as pdIf data is saved in the same working directory, open the file with the file name else use the complete file path.
data = pd.read_csv("file name/file path")***See for a sample project that includes Pandas.
Numpy is used for creating arrays (data with rows and colums), manipulating data (especially in data mining), and applying mathematical functions. Install numpy and check how to use numpy for further explanations.
Matplotlib is a static graphical library for creating visualizations. Visit matplotib For a quick start on matplotlib. You can also check my for sample work that included matplotlib
To be updated and continued