4.7 Introduction to Data Visualization - Python Programs

 

4.7 Introduction to Data Visualization

1. Write a Python program to draw a vertical bar chart showing the marks obtained by five students using Matplotlib. Give a suitable title and label both axes.

 

import matplotlib.pyplot as plt

students = ['Ram', 'Sita', 'Hari', 'Gita', 'Rita']

marks = [85, 90, 75, 95, 80]

plt.bar(students, marks, color='skyblue')

plt.xlabel('Students')

plt.ylabel('Marks')

plt.title('Marks Obtained by Students')

plt.show()

 

2. Write a Python program to display the marks obtained by five students using a Seaborn bar chart.

 

import seaborn as sns

import matplotlib.pyplot as plt

students = ['Ram', 'Sita', 'Hari', 'Gita', 'Rita']

marks = [85, 90, 75, 95, 80]

sns.barplot(x=students, y=marks, color='skyblue')

plt.xlabel('Students')

plt.ylabel('Marks')

plt.title('Marks Obtained by Students')

plt.show()

 

3. Write a Python program to draw an interactive bar chart showing the marks obtained by five students using Plotly Express.

 

import plotly.express as px

students = ['Ram', 'Sita', 'Hari', 'Gita', 'Rita']

marks = [85, 90, 75, 95, 80]

fig = px.bar(x=students, y=marks, title='Marks Obtained by Students', labels={'x': 'Students', 'y': 'Marks'})

fig.show()

 

4. Write a Python program to read student names and marks from a CSV file using Pandas and draw a vertical bar chart using Matplotlib.

 

import pandas as pd

import matplotlib.pyplot as plt

df = pd.read_csv('marks.csv')

plt.bar(df['Name'], df['Marks'], color='skyblue')

plt.xlabel('Students')

plt.ylabel('Marks')

plt.title('Student Marks from CSV')

plt.show()

5. Write a Python program to create a Pandas DataFrame containing student names and marks and draw a vertical bar chart using Matplotlib.

import pandas as pd

import matplotlib.pyplot as plt

data = {

    'Name': ['Ram', 'Sita', 'Hari', 'Gita', 'Rita'],

    'Marks': [85, 90, 75, 95, 80]

}

df = pd.DataFrame(data)

plt.bar(df['Name'], df['Marks'], color='skyblue')

plt.xlabel('Students')

plt.ylabel('Marks')

plt.title('Marks Obtained by Students')

plt.show()

 

6. Write a Python program to read student marks from a CSV file using Pandas and draw a bar chart using Seaborn.

import pandas as pd

import seaborn as sns

import matplotlib.pyplot as plt

df = pd.read_csv('marks.csv')

sns.barplot(data=df, x='Name', y='Marks', color='skyblue')

plt.xlabel('Students')

plt.ylabel('Marks')

plt.title('Student Marks from CSV')

plt.show()

 

7. Write a Python program to read student marks from a CSV file using Pandas and create an interactive bar chart using Plotly Express.

import pandas as pd

import plotly.express as px

df = pd.read_csv('marks.csv')

fig = px.bar(df, x='Name', y='Marks', title='Student Marks from CSV')

fig.show()

 

8. Write a Python program to draw a bar chart showing the marks of five students using different colors for each bar.

import matplotlib.pyplot as plt

students = ['Ram', 'Sita', 'Hari', 'Gita', 'Rita']

marks = [85, 90, 75, 95, 80]

colors = ['red', 'blue', 'green', 'orange', 'purple']

plt.bar(students, marks, color=colors)

plt.xlabel('Students')

plt.ylabel('Marks')

plt.title('Marks Obtained by Students')

plt.show()

9. Write a Python program to draw a line chart showing the monthly sales of a shop for five months: January (10000), February (15000), March (12000), April (18000) and May (22000). Use Matplotlib and give suitable labels and a title.

import matplotlib.pyplot as plt

months = ['Jan', 'Feb', 'Mar', 'Apr', 'May']

sales = [10000, 15000, 12000, 18000, 22000]

plt.plot(months, sales, marker='o', color='blue')

plt.xlabel('Months')

plt.ylabel('Sales (Rs.)')

plt.title('Monthly Sales with Markers')

plt.show()

 

10. Write a Python program to draw a line chart showing the monthly sales of a shop for five months using Seaborn. Give a suitable title and label both axes.

import seaborn as sns

import matplotlib.pyplot as plt

months = ['Jan', 'Feb', 'Mar', 'Apr', 'May']

sales = [10000, 15000, 12000, 18000, 22000]

sns.lineplot(x=months, y=sales, marker='o')

plt.xlabel('Months')

plt.ylabel('Sales (Rs.)')

plt.title('Monthly Sales Using Seaborn')

plt.show()

 

11. Write a Python program to draw an interactive line chart showing the monthly sales of a shop using Plotly Express. Include a suitable title, labels and markers.

import plotly.express as px

months = ['Jan', 'Feb', 'Mar', 'Apr', 'May']

sales = [10000, 15000, 12000, 18000, 22000]

fig = px.line(x=months,y=sales,markers=True,title='Monthly Sales',labels={'x': 'Months', 'y': 'Sales (Rs.)'})

fig.show()

 

12. A CSV file named sales.csv contains the monthly sales of a shop. Write a Python program to read the CSV file using Pandas and draw a line chart using Matplotlib. Give a suitable title and label both axes.

import pandas as pd

import matplotlib.pyplot as plt

df = pd.read_csv('sales.csv')

plt.plot(df['Month'], df['Sales'], marker='o')

plt.xlabel('Months')

plt.ylabel('Sales (Rs.)')

plt.title('Monthly Sales from CSV')

plt.show()

 

 

 

13. Write a Python program to read monthly sales data from a CSV file named sales.csv using Pandas and display a line chart using Seaborn. Include a suitable title and labels.

 

import pandas as pd

import seaborn as sns

import matplotlib.pyplot as plt

df = pd.read_csv('sales.csv')

sns.lineplot(data=df, x='Month', y='Sales', marker='o')

plt.xlabel('Months')

plt.ylabel('Sales (Rs.)')

plt.title('Monthly Sales from CSV')

plt.show()

 

14. Write a Python program to read monthly sales from a CSV file named sales.csv using Pandas and draw an interactive line chart using Plotly Express. Display markers and give a suitable title and labels.

 

import pandas as pd

import plotly.express as px

df = pd.read_csv('sales.csv')

fig = px.line(df, x='Month', y='Sales', markers=True, title='Monthly Sales from CSV', labels={'Month': 'Months', 'Sales': 'Sales (Rs.)'})

fig.show()

 

15. Write a Python program to draw a line chart showing monthly sales of a shop using Matplotlib. Display a red dashed line with circular markers. Give a suitable title and label both axes.

 

import matplotlib.pyplot as plt

months = ['Jan', 'Feb', 'Mar', 'Apr', 'May']

sales = [10000, 15000, 12000, 18000, 22000]

plt.plot(months, sales, color='red', linestyle='--', marker='o'

)

plt.xlabel('Months')

plt.ylabel('Sales (Rs.)')

plt.title('Monthly Sales')

plt.show()

 

16. Write a Python program to draw a pie chart showing the monthly household expenses of a family in five categories: Food (Rs. 12000), Rent (Rs. 20000), Transport (Rs. 5000), Education (Rs. 8000) and Others (Rs. 5000). Use Matplotlib, display category names and add a suitable title.

import matplotlib.pyplot as plt

categories = ['Food', 'Rent', 'Transport', 'Education', 'Others']

expenses = [12000, 20000, 5000, 8000, 5000]

plt.pie(expenses, labels=categories)

plt.title('Monthly Household Expenses')

plt.show()

17. Write a Python program to draw a pie chart showing the monthly expenses of a family using Matplotlib. Display the percentage of each category up to one decimal place, add labels and give a suitable title.

 

import matplotlib.pyplot as plt

categories = ['Food', 'Rent', 'Transport','Education', 'Others']

expenses = [12000, 20000, 5000, 8000, 5000]

plt.pie(expenses, labels=categories, autopct='%1.1f%%')

plt.title('Monthly Household Expenses')

plt.show()

 

19. Write a Python program to draw an interactive pie chart showing the monthly household expenses of a family using Plotly Express. Display category names and percentages with a suitable title.

 

import plotly.express as px

categories = ['Food', 'Rent', 'Transport', 'Education', 'Others']

expenses = [12000, 20000, 5000, 8000, 5000]

fig = px.pie(names=categories, values=expenses, title='Monthly Household Expenses')

fig.show()

 

20. A CSV file named expenses.csv contains household expense categories and their amounts. Write a Python program to read the CSV file using Pandas and draw a pie chart using Matplotlib. Display category names, percentages and a suitable title.

 

import pandas as pd

import matplotlib.pyplot as plt

df = pd.read_csv('expenses.csv')

plt.pie(

    df['Amount'],

    labels=df['Category'],

    autopct='%1.1f%%'

)

plt.title('Household Expenses from CSV')

plt.show()

 

22. Write a Python program to read the expenses.csv file using Pandas and create an interactive pie chart using Plotly Express. Display labels and percentages and give a suitable title.

 

import pandas as pd

import plotly.express as px

df = pd.read_csv('expenses.csv')

fig = px.pie(

    df,

    names='Category',

    values='Amount',

    title='Household Expenses from CSV'

)

fig.show()

 

23. Write a Python program to draw a pie chart showing household expenses using Matplotlib. Use different colors for each slice and display category names, percentages and a suitable title.

 

import matplotlib.pyplot as plt

categories = ['Food', 'Rent', 'Transport', 'Education', 'Others']

expenses = [12000, 20000, 5000, 8000, 5000]

colors = ['red', 'blue', 'green', 'orange', 'purple']

plt.pie(

    expenses,

    labels=categories,

    colors=colors,

    autopct='%1.1f%%'

)

plt.title('Monthly Household Expenses')

plt.show()

 

24. Write a Python program to draw a scatter plot showing the relationship between study hours and marks obtained by five students using Matplotlib. Give a suitable title and label both axes.

Study Hours	Marks
1	40
2	50
3	65
4	75
5	90

 

import matplotlib.pyplot as plt

hours = [1, 2, 3, 4, 5]

marks = [40, 50, 65, 75, 90]

plt.scatter(hours, marks, color='blue')

plt.xlabel('Study Hours')

plt.ylabel('Marks')

plt.title('Study Hours vs Marks')

plt.show()

 

25. Write a Python program to draw a scatter plot showing the relationship between study hours and marks obtained by five students using Seaborn. Add a title and appropriate axis labels.

 

import seaborn as sns

import matplotlib.pyplot as plt

hours = [1, 2, 3, 4, 5]

marks = [40, 50, 65, 75, 90]

sns.scatterplot(x=hours, y=marks, color='green')

plt.xlabel('Study Hours')

plt.ylabel('Marks')

plt.title('Study Hours vs Marks')

plt.show()

 

26. Write a Python program to draw an interactive scatter plot showing the relationship between study hours and marks using Plotly Express. Include a suitable title and labels.

 

import plotly.express as px

hours = [1, 2, 3, 4, 5]

marks = [40, 50, 65, 75, 90]

fig = px.scatter(

    x=hours,

    y=marks,

    title='Study Hours vs Marks',

    labels={'x': 'Study Hours', 'y': 'Marks'}

)

fig.show()

 

27. A CSV file named students.csv contains the study hours and marks obtained by five students. Write a Python program to read the CSV file using Pandas and draw a scatter plot using Matplotlib. Give a suitable title and label both axes.

 

import pandas as pd

import matplotlib.pyplot as plt

df = pd.read_csv('students.csv')

plt.scatter(df['Hours'], df['Marks'], color='blue')

plt.xlabel('Study Hours')

plt.ylabel('Marks')

plt.title('Study Hours vs Marks')

plt.show()

 

28. Write a Python program to draw a scatter plot showing the relationship between study hours and marks obtained by five students using Matplotlib. Use different colors and marker sizes for each point. Give a suitable title and label both axes.

 

import matplotlib.pyplot as plt

hours = [1, 2, 3, 4, 5]

marks = [40, 50, 65, 75, 90]

sizes = [100, 200, 300, 400, 500]

colors = ['red', 'blue', 'green', 'orange', 'purple']

plt.scatter(hours, marks, s=sizes, c=colors)

plt.xlabel('Study Hours')

plt.ylabel('Marks')

plt.title('Study Hours vs Marks')

plt.show()

 

 

29. A CSV file named students.csv contains the study hours and marks obtained by five students. Write a Python program to read the CSV file using Pandas and draw an interactive scatter plot using Plotly Express. Add a suitable title and axis labels.

 

import pandas as pd

import plotly.express as px

df = pd.read_csv('students.csv')

fig = px.scatter(

    df,

    x='Hours',

    y='Marks',

    title='Study Hours vs Marks',

    labels={'Hours': 'Study Hours', 'Marks': 'Marks'}

)

fig.show()

 

30. Write a Python program to read study hours and marks from a CSV file named students.csv using Pandas and draw a scatter plot using Seaborn. Give a suitable title and label both axes.

 

import pandas as pd

import seaborn as sns

import matplotlib.pyplot as plt

df = pd.read_csv('students.csv')

sns.scatterplot(data=df, x='Hours', y='Marks', color='green')

plt.xlabel('Study Hours')

plt.ylabel('Marks')

plt.title('Study Hours vs Marks')

plt.show()

 

31. Write a Python program to draw a scatter plot showing the relationship between study hours and marks obtained by five students using Matplotlib. Add grid lines, a suitable title and labels for both axes.

 

import matplotlib.pyplot as plt

hours = [1, 2, 3, 4, 5]

marks = [40, 50, 65, 75, 90]

plt.scatter(hours, marks, color='blue')

plt.xlabel('Study Hours')

plt.ylabel('Marks')

plt.title('Study Hours vs Marks')

plt.grid(True)

plt.show()