Last updated: 2023-08-15

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Knit directory: Pandas-30-R/

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In this repo, I provided a Python to R translation of 30 essential Pandas methods introduced by Avi Chawla in The Only 30 Methods You Should Master To Become A Pandas Pro published on TowardsDataScience.

The discussions of some of the methods went beyond the original, with more related methods illustrated/compared for more advanced or customized tasks (pls see specific methods highlighted in the list below). I will continue to add examples or relevant methods to enrich this site, as it now serves as a reference source for myself.

Hope you find it helpful too. Comments and suggestions are always appreciated. :)

Please click each method below for details

1. read_csv(): Reading a CSV

2. to_csv(): Storing a Dataframe into a CSV

3. DataFrame(): Creating a Dataframe from a Llist

4. DataFrame(): Creating a Dataframe from a Dictionary

5. shape: The Shape of the Dataframe

6. head(): Viewing Top N Rows

7. dtypes: Print the Datatype of Columns

8. astype() & pd.to_numeric(): Modifying the Datatype of a Column

9. info(): Printing Descriptive Info about the Dataframe (Method1)

10. describe(): Printing Descritive Info about the Dataframe (Method2)

11. fillna() & replace(): Filling Missing Values

12. merge & join: Joining DataFrames

13. sort_values(): Sorting a Dataframe

14. groupby(): Grouping a Dataframe

15. rename(): Renaming Columns

16-17. assign, lambda, iloc: Adding New Columns

18. query, filter, isin: Filtering a Dataframe1: Boolean filtering

19. filter & select_dtypes: Filtering a Dataframe2: Select columns

20. loc, map, set: Filtering a Dataframe3: Select by label

21. iloc: Filtering a Dataframe4: Select by position

22-23. unique & nunique: Finding Unique Values in a Dataframe

24. apply: Apply a Function to a Dataframe

25-26. duplicated & drop_duplicates: Handling Duplicates

27. value_counts, sidetable & tabyl: Standard and customized frequency tables

28. reset_index(drop, inplace): Resetting the index of a dataframe

29. crosstab(): Finding Cross-Tabulation

30. pivot_table & melt: Pivoting DataFrames

Bonus content 💃

The below content is not limited to pandas or tidyverse. Mainly useful stuff I learned along the way. :)

1. complete(): Expand a dataframe

2. datetime & dateutil: Working with dates in Python