106 ratings
4,078 already enrolled
Use a Filter to remove outliers in the data.
Combine the data using Pandas Merge.
Sort the data by rainfall and temperature.
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.
Data Science
merging
Python Programming
filtering
Pandas
In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:
Read the data into a Pandas DataFrame.
Use a Filter to remove outliers in the data.
Combine the data using Pandas Merge.
Sort the data by rainfall and temperature.
Use the Seaborn package to create a regression plot.
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
by DT
Nov 2, 2020Rhyme platform feels bug, demo video screen automatically becoming full screen it was really annoying and made coding uneasy. Please fix this.
by AT
Nov 6, 2020I loved this course because of the clarity and simplicity
by II
Sep 19, 2020You get what the title says! He also explains what we do why we do! so that's also good.
by SJ
Nov 2, 2020All doubts are clear and all concepts are explain in details ,happy to learn all new concepts.
Thank you.
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