Title | : | 3 Mistakes Data Scientists Make Leading to Missing Data |
Duration | : | 8m 56s |
Uploader | : | Data Science Bits |
Added On: | : | 01 September, 2020 |
Views | : | 131 times |
Likes | : | 26 |
Dislikes: | : | 0 |
Source | : | YouTube |
3 different mistakes we can make that will lead to missing data, by accident, after the data has been already collected. 🎥 Previous videos about Missing Data: The Origins of Missing Data https://youtu.be/rFbQCqiY8m4 Treat the Missing Data Well! https://youtu.be/7nbhvkxtYhw ► Feel free to send me questions over LinkedIn or YouTube comment sections! ► My Linktree profile: https://linktr.ee/felipepenha 🎓 🎓🎓 References 🎓🎓🎓 [1] Python package missingno: https://github.com/ResidentMario/missingno [3] SQL [various flavours] https://www.sqlite.org/index.html https://www.mysql.com/ https://www.postgresql.org/ [4] Pandas https://pandas.pydata.org/ [5] Koalas https://koalas.readthedocs.io/en/latest/ [6] Pyspark https://spark.apache.org/docs/latest/api/python/index.html [7] Tom Scott's video: The Worst Typo I Ever Made https://www.youtube.com/watch?v=X6NJkWbM1xk ✒️ Image Credits [1] Thumbnail picture: Photo by Tim Mossholder on Unsplash https://unsplash.com/photos/5EvOYDTolzE