Home > Introduction to Python > Introduction to data analysis with Pandas

Module: Introduction to Python

Topic: Introduction to data analysis with Pandas

1. Lesson: Introduction to numpy & pandas
2. Lesson: Working with data series
3. Lesson: Filtering & sorting
4. Lesson: Slicing & dicing
5. Lesson: Pivoting & unstacking

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Lesson 1

Introduction to numpy & pandas

Self Learning Duration

30 mins

Lecture Duration

60 mins

Self learning content

https://www.youtube.com/watch?v=5JnMutdy6Fw

Lecture content

Basic concepts of numpy & pandas.
Data series, numpy arrays

Lab and tutorials

None

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Lesson 2

Working with data series

Self Learning Duration

30 mins

Lecture Duration

120 mins

Self learning content

Lecture content

Creating and accessing data series and iterating through.

Lab and tutorials

None

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Lesson 3

Filtering & sorting

Self Learning Duration

30 mins

Lecture Duration

120 mins

Self learning content

https://pandas.pydata.org/pandas-docs/stable/user_guide/10min.html

Lecture content

Using conditions to filter data and do sorting.

Lab and tutorials

None

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Lesson 4

Slicing & dicing

Self Learning Duration

30 mins

Lecture Duration

240 mins

Self learning content

Lecture content

Getting different views, merging and manipulating. (alternatively Apply function).
Merging, Append and kind of joins (in merging).

Lab and tutorials

Use kaggle iris dataset and try to get different views from it. Come up with a scenario to do apply function as well.

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Lesson 5

Pivoting & unstacking

Self Learning Duration

30 mins

Lecture Duration

120 mins

Self learning content

https://pandas.pydata.org/pandas-docs/stable/user_guide/reshaping.html

Lecture content

Group by and pivots.
Aggregated functions and applying lambda on it.
Analizing a financial dataset to create differnt views can be hands on.

Lab and tutorials

None

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