How to Add Title to Pandas Plot?

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  • Post category:Pandas
  • Post last modified:October 4, 2023

In Pandas title arguments are used to add a title at the top of the plots. If a string is passed, print the string at the top of the figure. If a list is passed and subplots is True, print each item in the list above the corresponding subplot. In this article, I will explain how to add the title to the plots using title arguements.

1. Quick Example of How to Add Title to Pandas Plot

Below are quick Examples of how to add Title to Pandas plot.


# Following are the quick examples

# Example 1: create histogram with title
df.plot(kind = 'hist', title = 'Students Marks')

# Example 2: Create title of individual columns of histogram
 df.plot(kind='hist', subplots=True, title=['Maths', 'Physics', 'Chemistry'])

# Example 3: Get the individual column as a bar
df['death rate'].plot(kind="bar")

# Example 4: Set the labels and title
df['death rate'].plot(kind="bar", title="test")
plot.title("Death rate if corona virus")
plot.xlabel("Country")
plot.ylabel("Death Rate")

2. How to Add title to the Plots

In Python Pandas library is mainly focused for data analysis and it is not only a data visualization library but also using this we can create a basic plots. When we want to create exploratory data analysis plots, we can use Pandas is highly useful and practical. It provides several different functions to visualizing our data with the help of the plot() function. Use Pandas plot() function we can plot multiple variables of DataFrame.

Create a histogram using the pandas hist() method, which is a default method. For that, we need to create Pandas DataFrame using Python Dictionary. Let’s create DataFrame.


# Create DataFrame
import pandas as pd
import numpy as np
# Create DataFrame
df = pd.DataFrame({
    'Maths': [80.4, 50.6, 70.4, 50.2, 80.9],
    'Physics': [70.4, 50.4, 60.4, 90.1, 90.1],
    'Chemistry': [40, 60.5, 70.8, 90.88, 40],
    'Students': ['Student1', 'Student1', 'Student1', 'Student2', 'Student2']
})
print(df)

Yields below output.


# Output:
  Maths  Physics  Chemistry  Students
0   80.4     70.4      40.00  Student1
1   50.6     50.4      60.50  Student1
2   70.4     60.4      70.80  Student1
3   50.2     90.1      90.88  Student2
4   80.9     90.1      40.00  Student2

In order to plot a histogram in pandas using hist() function, DataFrame can call the hist(). It will return the histogram of each numeric column in the pandas DataFrame. For example,


# Create histogram with title
df.plot(kind = 'hist', title = 'Students Marks')
Pandas plot title
Histogram using pandas

3. Create Multiple Titles for Individual Subplots

The following code shows how to create individual titles for subplots in pandas:


# Create title of individual columns of histogram
 df.plot(kind='hist', subplots=True, title=['Maths', 'Physics', 'Chemistry'])
Pandas plot title
Individual columns of a histogram

4. Create Sample Plot Bar with Labels

Pandas provides different representations for showing the data in the form of graphs. One of the important diagrams is a Bar Plot and is rapidly used in many applications and presentations. We can make bar chart quickly and easily using data in Pandas DataFrames. Bar graph is one of the best for fast data exploration and comparison of variable values between different groups. A bar chart can be drawn directly using matplotlib, it can be drawn for the DataFrame columns using the DataFrame class itself

We can create a bar graph using a plot.bar() for, that we need to create Pandas DataFrame. Here I will create a single column DataFrame on world wide death rate of covid-19 in the pandemic. Here I have taken a list of country names as an index, it is set on an x-axis label and death rate as a measured value, is set on a y-axis label. For example,


# Create DataFrame
import matplotlib.pyplot as plt
import pandas as pd

df = pd.DataFrame({"death rate":[316.3, 321.3, 117.2, 38.25, 302.2 ]}, index = ["USA", "Brazil", "Germany", "India", "Uk"])
print(df)

# Draw a plot bar chart
df.plot.bar()

Yields below output.


# Output:
         death rate
USA          316.30
Brazil       321.30
Germany      117.20
India         38.25
Uk           302.20
Pandas plot
Bar chart of DataFrame

We can use the below syntax and get the individual columns on a plot bar of a given DataFrame. It is the same as Series are plotted in the same way.

We can use the below syntax and get the individual columns on a plot bar of a given DataFrame. It is the same as Series are plotted in the same way.


# Get the individual column as a bar
df['death rate'].plot(kind="bar")

5. Set the Axes Labeling & Set plot titles

If we give labeling of the x and y axis and set the title in a bar graph, it will give a better understanding to us. In Pandas plot(), labeling of the axis is done by using the Matplotlib syntax on the “plt” object imported from pyplot.

  • xlabel : It is used for set the label of x axis.
  • ylabel : It is used for set the label of y axis.
  • title : Using this we can set the title of bars

# Set the labels and title
df['death rate'].plot(kind="bar", title="test")
plt.title("Death rate of corona virus")
plt.xlabel("Country")
plt.ylabel("Death Rate")

Yields below output.

Pandas plot title
Pandas bar chart with xlabel, ylabel, and title, applied using Matplotlib pyplot interface.

6. Conclusion

In this article, I have explained how to add title to plots using pandas here, I have added the title to the histogram plots and bar graphs using title keyword.

Happy learning !!

References

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Vijetha

With 5 of experience in technical writing, I have had the privilege to work with a diverse range of technologies like Python, Pandas, NumPy and R. During this time, I have consistently demonstrated my ability to grasp intricate technical details and transform them into comprehensible materials.

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