Make your Data Science Workflow O.S.E.M.N!

It’s a pun. On the word awesome. You know? It’s punny!

https://www.google.com/url?sa=i&url=https%3A%2F%2Fgiphy.com%2Fgifs%2Fhuzzah-O1ibc4PRxKwrS&psig=AOvVaw1Es3jCvfo5Z5ue7bmCSFjR&ust=1592343654863000&source=images&cd=vfe&ved=0CAIQjRxqFwoTCODhucHkhOoCFQAAAAAdAAAAABAK
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Step 1a: Obtain your Data

https://www.google.com/url?sa=i&url=https%3A%2F%2Fgiphy.com%2Fexplore%2Fah-ha-ha&psig=AOvVaw1Fygx-KGu1EmlP-Edv8E0q&ust=1592344470056000&source=images&cd=vfe&ved=0CAIQjRxqFwoTCND3u8jnhOoCFQAAAAAdAAAAABAD
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Step 1b: Opening your Data

import pandas as pd
df = pd.read_csv(“winemag-data-130k-v2.csv”)
df.head()

Step 2: Scrubbing/Cleaning your Data — AKA Preprocessing

https://www.google.com/url?sa=i&url=https%3A%2F%2Ftvtropes.org%2Fpmwiki%2Fpmwiki.php%2FMain%2FJawDrop&psig=AOvVaw0riN131--gQKtZUYIc_L2W&ust=1592348013012000&source=images&cd=vfe&ved=0CAIQjRxqFwoTCLD-9Ov0hOoCFQAAAAAdAAAAABAD
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Step 3: Exploring your Data

https://www.google.com/url?sa=i&url=https%3A%2F%2Ftenor.com%2Fsearch%2Flets-explore-gifs&psig=AOvVaw2Zux-WPy4-p6xAm2T_f_Bn&ust=1592350487066000&source=images&cd=vfe&ved=0CAIQjRxqFwoTCJCCif79hOoCFQAAAAAdAAAAABAD

Step 4: Modeling your Data

https://www.google.com/url?sa=i&url=https%3A%2F%2Fgiphy.com%2Fgifs%2Fantmvh1-3ohzdMoc6rAljbqmg8&psig=AOvVaw3zxIcDJpkOwlXVZJlHiz1G&ust=1592351478785000&source=images&cd=vfe&ved=0CAIQjRxqFwoTCLDK-daBheoCFQAAAAAdAAAAABAD

Step 5: Interpret Results

Conclusion

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