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 arguments.
Key Points –
- Start by creating a plot using the
plot()
function provided by Pandas DataFrame. This function returns anAxesSubplot
object representing the plot. - Assign the result of the
plot()
function to a variable (often namedax
). This variable is anAxesSubplot
object that allows you to modify various aspects of the plot. - Alternatively, you can set the title directly in the
plot()
function by providing the title as an argument when calling the function. This can be a more concise way to add a title. - After setting the title, display the plot using
plt.show()
to visualize the changes made. This step is crucial for rendering the plot with the added title. - Use the
set_title()
method on theAxesSubplot
object to assign a title to the plot. Provide the desired title as an argument to this method.
1. Quick Example of Add Title to Pandas Plot
If you are in a hurry, below are some quick examples of how to add title to pandas plot.
# Quick example of add title to pandas plot
# 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')
3. Create Multiple Titles for Individual Subplots
The following code shows how to create individual titles for subplots in pandas. This program will create a histogram for each column in the DataFrame with individual titles for each subplot. Note that each subplot’s title is specified in the title
parameter as a list corresponding to the columns in the DataFrame.
# Create title of individual columns of histogram
df.plot(kind='hist', subplots=True, title=['Maths', 'Physics', 'Chemistry'])
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
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.
Frequently Asked Questions on How to Add Title to Pandas Plot
To add a title to a Pandas plot, you can use the set_title()
method on the AxesSubplot
object returned by the plot()
function. Alternatively, you can directly specify the title in the plot()
function.
You can add individual titles to subplots in a Pandas histogram. When using the plot()
function with the subplots=True
parameter, you can provide a list of titles using the title
parameter.
To set axis labels for a Pandas plot, you can use the set_xlabel()
and set_ylabel()
methods on the AxesSubplot
object. For example, ax.set_xlabel('X-axis Label')
and ax.set_ylabel('Y-axis Label')
will set the x and y-axis labels, respectively.
It is possible to customize the layout of subplots in a Pandas plot. The layout
parameter of the plot()
function allows you to specify the number of rows and columns for the subplot layout.
After making modifications to the plot, including adding a title, you should use plt.show()
to display the plot with the changes. This function is necessary to visualize the updated plot.
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 !!
Related Articles
- How to Plot Columns of Pandas DataFrame
- How to Plot the Pandas Series?
- How to Generate Time Series Plot in Pandas
- How to Plot a Scatter Plot Using Pandas?
- How to Change Pandas Plot Size?
- Create Pandas Plot Bar Explained with Examples
- How to Plot the Boxplot from DataFrame?
- How to Plot a Histogram Using Pandas?
- How to generate line plot in Pandas?
- How to add legends to plots in Pandas
- How to distribute column values in Pandas plot?
- How to make a histogram in Pandas Series?