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import pandas as pd

df = pd.read_csv("orders.csv", parse_dates=["order_date"])
df = df.drop_duplicates().dropna(subset=["amount"])

# revenue by month
monthly = (df.groupby(df["order_date"].dt.to_period("M"))
             ["amount"].sum())
print(monthly.tail(3))

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Five focused tracks, each built from practical tutorials you can follow on your own machine.

Python for Data

pandas, cleaning, dates, merging and charts.

SQL

Queries, joins, window functions and CTEs.

Machine Learning

Regression, metrics and validation done right.

AI Tools

LLM APIs, RAG, prompts and checking outputs.

Start here

New to data? Follow this path

Work through these six tutorials in order and you will be able to load, clean, summarise and query real data – and understand the first idea behind machine learning.

Read CSV files in pandasLoad data and fix the usual errors

Clean messy dataA practical cleaning checklist

Summarise with groupbyTurn rows into answers

Your first SQL queriesSELECT and WHERE from scratch

Join tables in SQLINNER, LEFT and the classic mistakes

Your first ML conceptWhy train/test splits matter

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Hi, I’m Lucky Joseph

I’m a UK-based writer with a data science background. DataScienceWay is where I publish practical, tested tutorials on the tools people actually use with data – explained honestly, including the parts that usually go wrong.

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