Here in this post, we will see how to plot a two bar graph on a different axis and multiple bar graph using Python’s Matplotlib library on a single axis. Let’s first understand what is a bar graph. We can use a bar graph to compare numeric values or data of different groups or we can say that A bar chart is a type of a chart or graph that can visualize categorical data with rectangular bars and can be easily plotted on a vertical or horizontal axis.

• Multiple Plots Python Pdf
• 2 Plots Python Tutorial
• 2 Plots Python Cheat
• 2 Subplots Python

Let’s see both in action:

Write a Python program to plot two or more lines on same plot with suitable legends of each line. Plt.GridSpec: More Complicated Arrangements¶. To go beyond a regular grid to subplots that span multiple rows and columns, plt.GridSpec is the best tool. The plt.GridSpec object does not create a plot by itself; it is simply a convenient interface that is recognized by the plt.subplot command. For example, a gridspec for a grid of two rows and three columns with some. Subplot(1,2,2) plot(y, x, 'g.-'); The good thing about the pylab MATLAB-style API is that it is easy to get started with if you are familiar with MATLAB, and it has a minumum of.

First of all, to create any type of bar graph whether it’s a single bar graph or a multiple bar graph, we need to import libraries that will help us to implement our task.

• Pandas library in this task will help us to import our ‘countries.csv’ file.
• From NumPy library, we will use np.arange() which will work similar to a range(10) = [0,1,2,3,4,5,6,7,8,9]
• And the final and most important library which helps us to visualize our data is Matplotlib. It will help us to plot multiple bar graph.

With the below lines of code, we can import all three libraries with their standard alias.

Second, we have to import the file which we need to visualize. If you want to download and use the CSV file, you can download it from here. We can use pandas .read_csv() function as shown below:

Now the question comes that we want to visualize is – The GDP and Population of the top 10 countries for the year 2007.

From the below code we have extracted the data only for the year 2007 and then sorted it according to the population. Also, we have taken top 10 values and stored it in the variable named datasort.

Now lets plot two bar graph or bar chart plots using the below code.

Plotting multiple bar graph using Python’s Matplotlib library:

The below code will create the multiple bar graph using Python’s Matplotlib library. Have a look at the below code:

Below you can see the multiple bar graph i.e for population and GDP on the same plot with two different x-axes on both the sides.

Hope you like our post. To learn more about Matplotlib package, you can go through the official documentation here.

A 2D density plot or 2D histogram is an extension of the well known histogram. It shows the distribution of values in a data set across the range of two quantitative variables. It is really

useful to avoid over plotting in a scatterplot. If you have too many dots, the 2D density plot counts the number of observations within a particular area of the 2D space. This specific area can be

a square or a hexagon (hexbin). You can also estimate a 2D kernel density estimation and represent it with contours.

Multiple Plots Python Pdf

Note that this online course has a chapter dedicated to 2D arrays visualization.

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From overlapping scatterplot to 2D density

Contour plot

2 Plots Python Tutorial

2D Histogram

Hexbin

2 Plots Python Cheat

2D Density

Marginal plots

If you have a huge amount of dots on your graphic, it is advised to represent the marginal distribution of both the X and Y variables. This is easy to do using the jointplot() function of the Seaborn library.

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2 Subplots Python