In this tutorial we’ll learn the basics of charting a bar graph out of a DataFrame using Python. If you are using Pandas for data wrangling, and all you need is a simple chart you can use the basic built-in Pandas plots. You can obviously use Matplotlib and Seaborn to draw more elaborated charts as needed.
Create Bar plot from Pandas DataFrame
Proceed as following to plot a bar chart in pandas:
- Create a pandas DataFrame from a file, database or dictionary.
- Use the DataFrame plot() method to define your chart.
- Customize your chart as needed by resizing it, add a legen, set your chart tile, set your axes ticks labels, etc’.
Importing data to the Python DataFrame
We’ll start with creating a pandas DataFrame by importing data using the read_csv() method.
import pandas as pd
my_df = pd.read_csv('interviews.csv')
print (my_df)Here’s our DataFrame populated with some hr interview data:
| language | first_interview | second_interview | |
|---|---|---|---|
| 1 | Kotlin | 70.0 | 81.0 |
| 2 | VisualBasic | 84.0 | 75.0 |
| 3 | PHP | 82.0 | 91.0 |
| 4 | Python | 86.0 | 81.0 |
Make a Bar graphs from a DataFrame
If we want to create a simple chart we can use the df.plot() method. Note that we’ll use the kind= parameter in order to specify the chart type. Several graphs are available such as histograms, pies, area, scatter, density etc’.
my_df.plot(kind='bar' , x='language');Here’s the early version of our very simple side by side bar chart:
Resize Pandas charts and adding a title
Modifying the Pandas chart size is easy using the figsize parameter. We are also use the title parameter to define the chart header content.
my_df.plot(kind='bar' , x='language', title='Interviews per month', figsize= (11,6));Here’s the chart:
Making an horizontal Python graph
By using the barh chart type, we can transpose the graph rendering.
my_df.plot(kind='barh' , x='language', title='Interviews per month');Stacked Python plot with Pandas
We can easily stack our bars chart as needed using the stacked parameter.
# stacked pandas bar graph
my_df.plot(kind='bar' , x='language', stacked=True, figsize= (11,6));Here’s the chart:
Change the color of our Python chart
The DataFrame.plot() method also delivers capability to map the chart to a known color map (cmap). Here’s an example:
#change color maps
my_df.plot(kind='bar' , x='language', stacked=True, cmap='Dark2',figsize= (11,6));And here’s the chart:
Modify the chart axes labels
We can also change the style of the axes labels. In this example we rotate the x-axis labels and enlarge the label font size.
my_df.plot(kind='bar' , x='language', stacked=True, cmap='Dark2', rot=30, fontsize=13, figsize= (11,6)));And here’s the output:
