Why Isn’t My Code Running After Installing Pandas, Numpy, and Matplotlib?

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What will you learn?

In this guide, you will uncover the reasons behind your Python code not running after installing Pandas, NumPy, and Matplotlib. You will explore troubleshooting steps to resolve common issues that may arise post-installation of these libraries.

Introduction to the Problem and Solution

Encountering issues where your Python code fails to execute after installing libraries like Pandas, NumPy, or Matplotlib can be frustrating. This guide aims to address the potential reasons behind this problem and provide solutions to ensure smooth functionality of these essential data science libraries in your projects.

When faced with code that doesn’t run after installing Pandas, NumPy, or Matplotlib, it’s crucial to consider various factors such as correct installation procedures and proper usage within your scripts. By following the troubleshooting steps outlined below, you can effectively diagnose and resolve common issues that may hinder the execution of your Python code.

Code

# Ensure successful import statements without errors
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

# Test basic functionality of each library
np_array = np.array([1, 2 ,3 ,4])
print("Numpy works:", np_array)

df = pd.DataFrame(np_array)
print("Pandas works:", df)

plt.plot(df)
plt.show()
print("Matplotlib works!")

# Copyright PHD

Explanation

To address why your Python code may not be running after installing Pandas, NumPy, and Matplotlib, we followed these steps:

  1. Understanding Import Errors:

    • Imported the libraries using standard aliases (pd for pandas, np for numpy, plt for matplotlib.pyplot) to check for any import errors.

  2. Testing Library Functionality:

    • Tested each library’s basic functionality:
      • Created an array using NumPy.
      • Wrapped the array in a DataFrame using Pandas.
      • Attempted plotting the DataFrame using Matplotlib.

These steps helped verify successful imports and operational status of each library within our environment.

  1. Why do I get “ModuleNotFoundError” even after installing a package?

  2. This error often occurs due to discrepancies between your working environment and where the package was installed (e.g., different Python versions).

  3. How can I check if my desired library is properly installed?

  4. You can use the pip list command in the terminal/command prompt to display all currently installed packages.

  5. What should I do if my script runs fine but nothing displays?

  6. Ensure plt.show() is called at the end of plotting commands when dealing with graphical outputs like plots from Matplotlib.

  7. Can incorrect versions of these libraries cause compatibility issues?

  8. Yes! Always refer to documentation for version compatibility when working with multiple complex packages simultaneously.

  9. How do I update my existing packages like Pandas or Numpy?

  10. You can update packages by running:

  11. pip install --upgrade pandas numpy matplotlib
  12. # Copyright PHD
Conclusion

Troubleshooting why your Python code isn�t running after installing data science libraries involves verifying environmental setup and correct installation paths while ensuring proper syntax within scripts. By starting with simple checks like confirming installations via pip list command and examining error messages during execution, you can identify and resolve issues effectively.

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