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Python for Data Analysis

  • Number of Courses33 courses
  • Duration31 hours
  • Skill IQ available Skill IQ

Python is one of the most popular and powerful programming languages data analysts use to process, analyze, and visualize data efficiently. Data analysts leverage Python's extensive libraries such as pandas for data manipulation, NumPy for numerical operations, and Matplotlib for creating charts. These tools enable analysts to clean data, perform exploratory data analysis, and generate actionable insights, making Python an essential skill in data-driven industries to support analytics and inform business decisions.

This learning path is intended for anyone who wants to level up their data analysis skills with Python.

Courses in this path

Python: Importing Data

Importing data with Python is an important pre-requisite to actually working with that data in Python. These courses teach you how to read and import data from various sources using Python.

Python: NumPy

NumPy is critical for numerical computations in Python. The courses teach you the foundational concepts necessary before moving on to more complex data manipulation with pandas.

Python: Cleaning Data

Cleaning data is a critical part of data analysis using Python. The courses in this section teach you how to handle missing values, outliers, and errors commonly found in data sets.

Python: Data Wrangling

Data wrangling involves transforming and mapping data from one "raw" data format into another that may be more appropriate for analysis. The courses in this section teach you how to wrangle your data with Python effectively.

Python: Advanced Pandas

Build upon the knowledge you learned in the pandas essentials section of this learning path.

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