Thread by @NainaChaturved8

Pandas is a fast, powerful, flexible and open source data analysis and manipulation tool.

A Mega thread 🧵covering 10 amazing Pandas hacks and how to efficiently use it(with Code Implementation)👇🏻
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1/ Indexing data frames
Indexing means to selecting all/particular rows and columns of data from a DataFrame. In pandas it can be done using two constructs —
.loc() : location based
It has methods like scalar label, list of labels, slice object etc
.iloc() : Interger based

2/ Slicing data frames
In order to slice by labels you can use loc() attribute of the DataFrame.

Implementation —

3/ Filtering data frames
Using Filter you can subset rows or columns of dataframe according to labels in the specified index of the data.

Implementation —

4/ Transforming Data Frames
Pandas Transform helps in creating a DataFrame with transformed values and has the same axis length as its own.

Implementation —

5/ Adding Rows — append()

Implementation —

6. Hierarchical indexing
Hierarchical indexing is the technique in which we set more than one column name as the index. set_index() function is used for when doing hierarchical indexing.

Implementation —

7/ Merging data frames
Concat() Function is used to merge the dataframes.

Implementation --

8/ Joins —
It helps us merging DataFrames. Types of Joins —
Inner Join :- Returns records that have matching values in both tables.
Left Join :- Returns all the rows from the left table that are specified in the left outer join clause, not just the rows in which the columns match

9/ Right Join :- Returns all records from the right table, and the matched records from the left table.
Full Join :- Returns all records when there is a match in either left or right table.
Cross Join :- Returns all possible combinations of rows from two tables.

Implementation-

10/ Pivot Tables
It creates a Spreadsheet style pivot table as a DataFrame.

Implementation -

11/ Aggregate Functions
Pandas has a number of aggregating functions that reduce the dimension of the grouped object.
count()
value_count()
mean()
median()
sum()
min()
max()
std()
var()
describe()
sem()

Implementation -

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