Plotting Bar Charts from Pandas DataFrames

In this article, we will discuss how to plot bar charts from Pandas dataframes. Specifically, we will cover how to properly plot a bar chart for a specific student from user input.

Understanding the Problem

The problem arises when trying to plot a bar chart for a single student’s exams from a Pandas dataframe. The x-values of the plot are being used as tick labels on the x-axis, which is causing issues with the appearance of the graph.

For example, consider the following code snippet:

import pandas as pd
import matplotlib.pyplot as plt

df = pd.DataFrame({'student_id': [83838, 16373, 93538, 29383, 58585],
                   'exam_1': [80, 95, 90, 75, 50],
                   'exam_2': [60, 92, 88, 85, 40],
                   'exam_3': [70, 55, 75, 45, 60],
                   'exam_4': [55, 95, 45, 80, 55],
                   'exam_5': [91, 35, 92, 90, 75]})

print(df)

df = df.loc[df['student_id'] == 29383]
print(df)

exam_plots_for_29383 = df.plot.bar()
plt.show()

df = df.T
exam_plots_for_29383_T = df.plot.bar()
plt.show()  

This code will produce a bar plot with the student’s ID as tick labels on the x-axis, which is not what we want.

Solution

To fix this issue, we need to set the ‘student_id’ column as the index of the dataframe. This way, it won’t be plotted and we can use the index to select specific rows for plotting.

Here’s how you can do it:

df = df.set_index('student_id')

Then, you can plot the bar chart using the plot function with the kind='bar' argument. To specify a particular row, you can use the .loc method.

For example:

df.loc[29383].plot(kind='bar', figsize=(4,3), rot=30)

This will plot a bar chart for the specific student’s exams with their IDs on the x-axis and their values on the y-axis.

Adding Color to the Bar Chart

If you want to color each exam differently, you can use a categorical color palette. For example:

from matplotlib import cm

df.loc[29383].plot(kind='bar', figsize=(4,3), rot=30, color=cm.tab10.colors[0:5])

This will plot the bar chart with five different colors for each exam.

Creating a Bar Chart for Each Student

To create a bar chart for each student from user input, you can use the .loc method to select the rows based on the student ID. Here’s an example:

import matplotlib.pyplot as plt

# Get the list of unique student IDs
student_ids = df.index.unique()

for student_id in student_ids:
    print(f"Plotting bar chart for student {student_id}")
    
    # Set the index to the current student ID
    df = df.set_index('student_id')
    
    # Plot the bar chart
    plt.figure(figsize=(4,3))
    df.loc[student_id].plot(kind='bar', rot=30)
    
    # Add title and labels
    plt.title(f"Bar Chart for Student {student_id}")
    plt.xlabel("Exam")
    plt.ylabel("Score")
    
    # Show the plot
    plt.show()

This code will create a bar chart for each student in the dataframe, with their IDs on the x-axis and their values on the y-axis.

Conclusion

In this article, we covered how to properly plot bar charts from Pandas dataframes. We discussed how to set the ‘student_id’ column as the index of the dataframe and use it to select specific rows for plotting. We also showed how to add color to the bar chart using a categorical color palette. Finally, we created a bar chart for each student in the dataframe from user input.

Additional Resources

For more information on Pandas and Matplotlib, please see:

• Pandas documentation
• Matplotlib documentation

Last modified on 2023-12-23