explanation each code line by line experiment 1b - FarhaKousar1601/DATA-SCIENCE-AND-ITS-APPLICATION-LABORATORY-21AD62- GitHub Wiki

Aim

For the given dataset mtcars.csv (available at www.kaggle.com/ruiromanini/mtcars), plot a histogram to check the frequency distribution of the variable 'mpg' (Miles per gallon).

Code Explanation

import pandas as pd
import matplotlib.pyplot as plt

# Load the dataset
mtcars = pd.read_csv('mtcars.csv')  # Replace 'path_to_your_mtcars.csv' with the actual path to your mtcars.csv file

# Plotting the histogram
plt.hist(mtcars['mpg'], bins=10, color='skyblue', edgecolor='black')

# Adding labels and title
plt.xlabel('Miles per gallon (mpg)')
plt.ylabel('Frequency')
plt.title('Histogram of Miles per gallon (mpg)')

# Displaying the plot
plt.show()

Explanation of Each Line

Importing the Required Libraries

import pandas as pd
import matplotlib.pyplot as plt
  • import is a statement used to include external libraries or modules in your code.
  • Pandas (pd) is a powerful data manipulation and analysis library for Python.
  • Matplotlib (plt) is a comprehensive library for creating static, animated, and interactive visualizations in Python.

Loading the Dataset

mtcars = pd.read_csv('mtcars.csv')  # Replace 'path_to_your_mtcars.csv' with the actual path to your mtcars.csv file
  • pd.read_csv() is a function used to read a CSV file into a DataFrame.
  • 'mtcars.csv' is the filename. Replace it with the actual path to your mtcars.csv file if it's located elsewhere.
  • mtcars is the DataFrame containing the data from the mtcars.csv file.

Plotting the Histogram

plt.hist(mtcars['mpg'], bins=10, color='skyblue', edgecolor='black')
  • plt.hist() is a function used to create a histogram.
  • mtcars['mpg'] specifies the data for the histogram, which is the 'mpg' (Miles per gallon) column from the mtcars DataFrame.
  • bins=10 sets the number of bins (intervals) for the histogram.
  • color='skyblue' sets the color of the bars.
  • edgecolor='black' sets the color of the edges of the bars for better visibility.

Adding Labels and Title

plt.xlabel('Miles per gallon (mpg)')
plt.ylabel('Frequency')
plt.title('Histogram of Miles per gallon (mpg)')
  • plt.xlabel() sets the label for the x-axis.
  • plt.ylabel() sets the label for the y-axis.
  • plt.title() sets the title for the plot.

Displaying the Plot

plt.show()
  • plt.show() renders the plot and displays it on the screen.

Library Definitions

Pandas

  • Pandas is a fast, powerful, flexible, and easy-to-use open-source data analysis and manipulation library built on top of the Python programming language.

Matplotlib

  • Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations in Python.
  • Pyplot is a module in Matplotlib used for making simple plots like line charts, bar charts, histograms, and more.

Questions and Answers

What does import pandas as pd do?

  • It imports the Pandas library and assigns it the alias pd for easier usage in the code.

What does import matplotlib.pyplot as plt do?

  • It imports the pyplot module from the matplotlib library and assigns it the alias plt for easier usage in the code.

What is the purpose of pd.read_csv()?

  • pd.read_csv() reads a CSV file and loads its contents into a DataFrame.

How do we plot a histogram using Matplotlib?

  • We use plt.hist() to create a histogram, specifying the data, the number of bins, and other formatting options.

How do we add labels and a title to the plot?

  • We use plt.xlabel() to set the x-axis label, plt.ylabel() to set the y-axis label, and plt.title() to set the title of the plot.

How do we display the plot on the screen?

  • We use plt.show() to render the plot and display it on the screen.