Install Python Package | Jupyter Notebook Tutorial (2026) | Step-by-Step Guide

Install Python Package | Jupyter Notebook Tutorial (2026) | Step-by-Step Guide¶

Below is a Step-by-Step Guide on How to Install and work with Python Packages numpy, pandas, matplotlib in Jupyter Notebook:
numpy: Fundamental package for array computing in Python.
pandas: Powerful data structures for data analysis, data manipulation, time series, and statistics.
matplotlib: Python plotting package for creating charts and graphs.
(Run each cell by pressing Shift + Enter)

1. Install Packages¶

📌Check if package numpy, pandas and matplotlib is installed using command:

In [1]:

%pip show numpy pandas matplotlib

Note: you may need to restart the kernel to use updated packages.

WARNING: Package(s) not found: matplotlib, numpy, pandas

📌Install package numpy:

In [2]:

%pip install numpy

Collecting numpy
  Using cached numpy-2.5.4-cp314-cp314-win_amd64.whl.metadata (6.6 kB)
Using cached numpy-2.5.4-cp314-cp314-win_amd64.whl (12.7 MB)
Installing collected packages: numpy
Successfully installed numpy-2.5.4
Note: you may need to restart the kernel to use updated packages.

📌Install both packages pandas and matplotlib:

In [ ]:

%pip install pandas matplotlib

📌Jupyter will download and install the package. Wait until the installation process finishes.

📌Check if package numpy, pandas and matplotlib is installed successfully using command:

In [ ]:

%pip show numpy pandas matplotlib

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2. Install Package of a Specific Version¶

📌If your project requires a particular version of a package, specify the version number:

In [6]:

%pip install pandas==3.0.2

Collecting pandas==3.0.2
  Using cached pandas-3.0.2-cp314-cp314-win_amd64.whl.metadata (19 kB)
Requirement already satisfied: numpy>=2.3.3 in C:\Users\schol\miniconda3\envs\jn\Lib\site-packages (from pandas==3.0.2) (2.5.4)
Requirement already satisfied: python-dateutil>=2.8.2 in C:\Users\schol\miniconda3\envs\jn\Lib\site-packages (from pandas==3.0.2) (2.9.0.post0)
Requirement already satisfied: tzdata in C:\Users\schol\miniconda3\envs\jn\Lib\site-packages (from pandas==3.0.2) (2026.2)
Requirement already satisfied: six>=1.5 in C:\Users\schol\miniconda3\envs\jn\Lib\site-packages (from python-dateutil>=2.8.2->pandas==3.0.2) (1.17.0)
Using cached pandas-3.0.2-cp314-cp314-win_amd64.whl (9.9 MB)
Installing collected packages: pandas
  Attempting uninstall: pandas
    Found existing installation: pandas 3.0.6
    Uninstalling pandas-3.0.6:
      Successfully uninstalled pandas-3.0.6
Successfully installed pandas-3.0.2
Note: you may need to restart the kernel to use updated packages.

In [ ]:

%pip show pandas

📌To upgrade an existing package to a newer available version:

In [8]:

%pip install --upgrade pandas

Requirement already satisfied: pandas in C:\Users\schol\miniconda3\envs\jn\Lib\site-packages (3.0.2)
Collecting pandas
  Using cached pandas-3.0.6-cp314-cp314-win_amd64.whl.metadata (19 kB)
Requirement already satisfied: numpy>=2.3.3 in C:\Users\schol\miniconda3\envs\jn\Lib\site-packages (from pandas) (2.5.4)
Requirement already satisfied: python-dateutil>=2.8.2 in C:\Users\schol\miniconda3\envs\jn\Lib\site-packages (from pandas) (2.9.0.post0)
Requirement already satisfied: tzdata in C:\Users\schol\miniconda3\envs\jn\Lib\site-packages (from pandas) (2026.2)
Requirement already satisfied: six>=1.5 in C:\Users\schol\miniconda3\envs\jn\Lib\site-packages (from python-dateutil>=2.8.2->pandas) (1.17.0)
Using cached pandas-3.0.6-cp314-cp314-win_amd64.whl (9.8 MB)
Installing collected packages: pandas
  Attempting uninstall: pandas
    Found existing installation: pandas 3.0.2
    Uninstalling pandas-3.0.2:
      Successfully uninstalled pandas-3.0.2
Successfully installed pandas-3.0.6
Note: you may need to restart the kernel to use updated packages.

In [ ]:

%pip show pandas

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3. Import Packages and Test¶

📌Import Packages and Test it using below command:

In [10]:

import numpy as np
import pandas as pd

In [11]:

print(np.__version__)
print(pd.__version__)

2.5.4
3.0.6

📌If a version number appears without an error, the package is installed and working.

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4. Extracting Data from a CSV File Using Pandas¶

📌Create a csv file TestFile.csv
📌The below example code reads the CSV file and displays its contents.

In [12]:

data = pd.read_csv("TestFile.csv")
data.head()

Out[12]:

	Product_ID	Product_Name	Category	Price	Quantity	Total
0	101	Laptop	Electronics	55000	2	110000
1	102	Mouse	Accessories	750	5	3750
2	103	Keyboard	Accessories	1500	3	4500

📌pd.read_csv("TestFile.csv") → Reads the CSV file and returns its contents as a DataFrame.
data → variable that stores the Pandas DataFrame.
data.head() → Displays the first five rows of the DataFrame.

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5. Visualizing Data Using Matplotlib¶

📌The below example code creates and displays a line graph:

In [13]:

import matplotlib.pyplot as plt
plt.plot([1,2,3],[4,5,6])
plt.show()

📌pyplot is a module inside Matplotlib which is imported.
📌The plot() function takes two lists and creates a line graph:
First list [1, 2, 3] represents the X-axis values.
Second list [4, 5, 6] represents the Y-axis values.
📌The show() function displays the graph.
📌This code draws a line graph connecting the points (1, 4), (2, 5), and (3, 6).

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