Dataframe

1. DataFrame (Class 12 Python
Pandas)
– A DataFrame is a 2D labeled data structure.
– It consists of rows and columns.
– Part of the Pandas library.

2. Features of DataFrame
– Two dimensional
‑
– Heterogeneous data
– Mutable
– Labeled rows and columns

3. Creating DataFrame – From List
– Using: pd.DataFrame(list)
– Example included in later slides

4. Creating DataFrame – From
Dictionary of Lists
– Each key becomes a column
– Each value is a list of column entries

5. Creating DataFrame – From
Dictionary of Series
– Series objects combine into a DataFrame

6. Creating DataFrame – From List of
Dictionaries
– Each dictionary becomes a row

7. Attributes of DataFrame
– shape
– size
– values
– columns
– index

8. Attribute: shape
– Returns number of rows and columns

9. Attribute: size
– Returns total number of elements

10. Attribute: columns
– Gives list of column labels

11. Attribute: index
– Gives row labels

12. Accessing Data in DataFrame
– Column access: df['col']
– Row access: loc & iloc

13. loc[]
– Label-based data selection

14. iloc[]
– Index-based data selection

15. Adding Columns
– Direct assignment: df['new']=value

16. Deleting Columns
– Using del df['col']
– or df.drop()

17. Adding Rows
– Using loc
– or append (deprecated)

18. Deleting Rows
– Using df.drop(index)

19. Operations on DataFrame
– head(), tail()
– describe()
– sum()
– mean()

20. Example Code
– import pandas as pd
– data={'Name':['A','B'], 'Marks':[90,85]}
– df=pd.DataFrame(data)
– print(df)

21. Real Life Use
– Used in data analysis
– Machine learning
– Handling tabular data

22. End
– Thank you!