msb-public
/
Data-Science-For-Beginners
mirror of https://github.com/microsoft/Data-Science-For-Beginners.git
1
0
Code Issues Projects Releases Wiki Activity

Update README.md

Browse Source
pull/118/head
Anupam Mishra 4 years ago committed by GitHub
parent ddcad74acb
commit 50f1cad5a7
No known key found for this signature in database
GPG Key ID: 4AEE18F83AFDEB23
1 changed files with 5 additions and 5 deletions
Show Stats Download Patch File Download Diff File

8
2-Working-With-Data/08-data-preparation/README.md
Unescape View File

@ -4,9 +4,9 @@
|:---:| |:---:|
|Data Preparation - _Sketchnote by [@nitya](https://twitter.com/nitya)_ | |Data Preparation - _Sketchnote by [@nitya](https://twitter.com/nitya)_ |
## Pre-Lecture Quiz ## [Pre-Lecture Quiz](https://red-water-0103e7a0f.azurestaticapps.net/quiz/14)
[Pre-lecture quiz](https://red-water-0103e7a0f.azurestaticapps.net/quiz/14)
Depending on its source, raw data may contain some inconsistencies that will cause challenges in analysis and modeling. In other words, this data can be categorized as “dirty” and will need to be cleaned up. This lesson focuses on techniques for cleaning and transforming the data to handle challenges of missing, inaccurate, or incomplete data. Topics covered in this lesson will utilize Python and the Pandas library and will be [demonstrated in the notebook](notebook.ipynb) within this directory. Depending on its source, raw data may contain some inconsistencies that will cause challenges in analysis and modeling. In other words, this data can be categorized as “dirty” and will need to be cleaned up. This lesson focuses on techniques for cleaning and transforming the data to handle challenges of missing, inaccurate, or incomplete data. Topics covered in this lesson will utilize Python and the Pandas library and will be [demonstrated in the notebook](notebook.ipynb) within this directory.
@ -33,9 +33,9 @@ Depending on its source, raw data may contain some inconsistencies that will cau
Give the exercises in the [notebook](4-Data-Science-Lifecycle\15-analyzing\notebook.ipynb) a try! Give the exercises in the [notebook](4-Data-Science-Lifecycle\15-analyzing\notebook.ipynb) a try!
## Post-Lecture Quiz ## [Post-Lecture Quiz](https://red-water-0103e7a0f.azurestaticapps.net/quiz/15)
[Post-lecture quiz](https://red-water-0103e7a0f.azurestaticapps.net/quiz/15)
## Review & Self Study ## Review & Self Study

Write Preview
Loading…
Cancel
Save