Pandas
Clean, transform, analyze, and reshape real-world datasets.
Course overview
Pandas is the premier data manipulation library for data science and analytics in Python. In this course, you will learn to load data from CSVs and databases, clean dirty records, handle missing values, transform columns, group and aggregate data, and pivot complex tables.
Prerequisites
What you'll achieve
- Work fluently with Pandas Series and DataFrames
- Ingest, clean, inspect, and export tabular datasets
- Handle missing values, duplicate records, and data type conversions
- Perform sophisticated grouping, aggregations, joins, and pivots
Curriculum
- 1Pandas architecture: Series vs. DataFrames
- 2Reading & writing data (CSV, Excel, JSON, SQL)
- 3Data inspection: head(), info(), describe(), value_counts()
- 4Filtering, indexing & slicing with .loc[] and .iloc[]
- 5Data cleaning: Handling nulls (fillna, dropna), duplicates & string methods
- 6Groupby operations and aggregate statistics
- 7Merging, joining & concatenating multiple DataFrames
- 8Project: Comprehensive data cleaning & analysis of a messy real-world dataset
Who is this for?
Data analysts, researchers, students, and Python developers entering data careers.
Contact admissions for current fee and available learning formats
Enrol in Pandas
- 5 weeks
- Beginner to Intermediate
- Live online · One-to-one available · Group batches when scheduled
- 1-on-1 & small batches
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Ready to start your learning journey?
Apply today and our admissions team will review your application and guide you through the next steps.