Merge, Sort and Filter Data in Python Pandas

Offered By
Coursera Project Network
In this Guided Project, you will:

Use a Filter to remove outliers in the data.

Combine the data using Pandas Merge.

Sort the data by rainfall and temperature.

Clock1 hour
IntermediateIntermediate
CloudNo download needed
VideoSplit-screen video
Comment DotsEnglish
LaptopDesktop only

Visualizing data patterns often involves re-arrangement and elimination to determine patterns. For example, in a list of data with yearly rainfall amounts, to quickly determine the years with the most rainfall, the data can be sorted according to rainfall in descending order. A filter could be used to limit the amount of data observed, for example, to only show rainfall amounts greater than an inch. A merge can be used to join two datasets together, for example rainfall and temperature data from two different sources. The ability to sort, merge and filter data has always existed using SQL with database data, now it can be done in application memory space using Python. In this course, you will create an application that reads data from two CSV files. You will learn how to merge, sort, and filter the data to ultimately produce a regression plot to determine a possible correlation between two data sets.

Skills you will develop

Data SciencemergingPython ProgrammingfilteringPandas

Learn step-by-step

In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:

  1. Read the data into a Pandas DataFrame.

  2. Use a Filter to remove outliers in the data.

  3. Combine the data using Pandas Merge.

  4. Sort the data by rainfall and temperature.

  5. Use the Seaborn package to create a regression plot.

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Your workspace is a cloud desktop right in your browser, no download required

In a split-screen video, your instructor guides you step-by-step

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