How To Creating Our First Pandas Data Frame | Pandas Tutorial 1 | Big Data Tutorials | Codeing School

This is Pandas Tutorial Part 1. pandas is an open source, BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language.

Creating Our First Pandas Data Frame | Pandas Tutorial Part 1

Today’ Topic: We create Data Frame for pandas.

Without DataFrame we can’t assess our data. Without DataFrame we can’t load your data in RAM easily.   

Without pandas, we can load data in RAM, but this is not easy prose.  

Open your Jupyter Notebook.

Import pandas and numpy

Import pandas as pd

Import numpy as np

import pandas and numpy

Create Empty DataFrame:

df = pd.DataFrame()

df

Output

Empty DataFrame

Columns: []

Index: []

Empty DataFrame

Logic: We create an empty data frame. We need to create an empty in projects, because, we can store data in the empty data frame and append this stored data. Moreover, for dynamically data append for uses.

Create a DataFrame:

df1=pd.DataFrame([[1,2,3,4],[5,6,7,8],[9,10,23,123],[23,235,123,634],[12,23,42,11]])

df1

Output:

	0	1	2	3
0	1	2	3	4
1	5	6	7	8
2	9	10	23	123
3	23	235	123	634
4	12	23	42	11

Create DataFrame

Logic: Jupyter is very smart it arrange the data in rows and columns.

Print First Three Rows:

df1.head(3)

Output

	0	1	2	3
0	1	2	3	4
1	5	6	7	8
2	9	10	23	123

Print 1st 3 Rows

Logic: df1.head(3), this means we print 1^st 3 rows.

Print last 4 rows

df1.tail(4)

Output

	0	1	2	3
1	5	6	7	8
2	9	10	23	123
3	23	235	123	634
4	12	23	42	11

Print last 4 rows

Logic: df1.tail(4), this means we print last 4 rows.

If you have any quarry, please comment below.