Bar Chart Using Pandas DataFrame In Python

Overview:

  • A bar chart displays a set of categories in one axis and the percentage or frequencies of a variable for those categories in another axis.
  • The height of the bar is either less or more depending upon the frequency value.
  • In a Vertical Bar Chart, the X-axis will represent categories and Y-axis will represent frequencies. In a Horizontal Bar Chart, it is the inverse.
  • In a Vertical Bar Chart, the bars grow downwards below the X-axis for negative values.
  • In a Horizontal Bar Chart, the bars grow leftwards from the Y-axis for negative values.

 

Plotting Bar charts using pandas DataFrame:

  • While a bar chart can be drawn directly using matplotlib, it can be drawn for the DataFrame columns using the DataFrame class itself. 
  • The pandas DataFrame class in Python has a member plot. Using the plot instance various diagrams for visualization can be drawn including the Bar Chart.
  • The bar() method draws a vertical bar chart and the barh() method draws a horizontal bar chart.
  • The bar() and barh() of the plot member accepts X and Y parameters. By default, X takes the index of the DataFrame and all the numeric columns are drawn as Y.
  • Any keyword argument supported by the method DatFrame.plot() can be passed to the bar() method in order to customize the bar chart. For example, the keyword argument title places a title on top of the bar chart.
  •  

Example – Bar Chart of a pandas DataFrame: one column as X-axis and another as Y-axis:

import pandas as pd

import matplotlib.pyplot as plot

 

# A python dictionary

data = {"City":["London", "Paris", "Rome"],

        "Visits":[20.42,17.95,9.7]

        };

# Dictionary loaded into a DataFrame       

dataFrame = pd.DataFrame(data=data);

 

# Draw a vertical bar chart

dataFrame.plot.bar(x="City", y="Visits", rot=70, title="Number of tourist visits - Year 2018");

plot.show(block=True);

 

Output:

Vertical bar chart using Pandas DataFrame

 

Compound Bar Chart or Nested Bar Chart:

The following Python code plots a compound bar chart combining two variables Car Price, Kerb Weight for the sedan variants produced by a car company.

Example:

# Example Python program to plot a complex bar chart 

import pandas as pd

import matplotlib.pyplot as plot

 

# A python dictionary

data = {"Car Price":[24050, 34850, 38150],

        "Kerb Weight":[3045, 3572, 3638]

        };

index     = ["Variant1", "Variant2", "Variant3"];

 

# Dictionary loaded into a DataFrame       

dataFrame = pd.DataFrame(data=data, index=index);

 

# Draw a vertical bar chart

dataFrame.plot.bar(rot=15, title="Car Price vs Car Weight comparision for Sedans made by a Car Company");

plot.show(block=True);

Output:

Drawing a Compound Bar Chart using pandas

Stacked vertical bar chart:

A stacked bar chart illustrates how various parts contribute to a whole. The example Python code plots a pandas DataFrame as a stacked vertical bar chart. The Python code plots two variables - number of articles produced and number of articles sold for each year as stacked bars. The years are plotted as categories on which the plots are stacked.

Example:

# Example Python program to plot a stacked vertical bar chart 

import pandas as pd

import matplotlib.pyplot as plot

 

# A python dictionary

data = {"Production":[10000, 12000, 14000],

        "Sales":[9000, 10500, 12000]

        };

index     = ["2017", "2018", "2019"];

 

# Dictionary loaded into a DataFrame

dataFrame = pd.DataFrame(data=data, index=index);

 

# Draw a vertical bar chart

dataFrame.plot.bar(stacked=True,rot=15, title="Annual Production Vs Annual Sales");

plot.show(block=True);

 

Output:

Stacked Vertical Bar Chart drawn using a pandas DataFrame in Python

Horizontal Bar Chart:

  • In a horizontal bar chart categories are drawn in Y-axis and the frequencies of the variables for the categories are drawn in X-axis.

  • The Python example code plots the Growth Rate of different countries from a pandas DataFrame into a horizontal bar chart.

Example:

# Example python program to plot a horizontal bar chart

import pandas as pd

import matplotlib.pyplot as plot

 

growthData = {"Countries": ["Country1", "Country2", "Country3", "Country4", "Country5", "Country6", "Country7"],

              "Growth Rate":[10.2, 7.5, 3.7, 2.1, 1.5, -1.7, -2.3]};

dataFrame  = pd.DataFrame(data = growthData);

dataFrame.plot.barh(x='Countries', y='Growth Rate', title="Growth rate of different countries");

plot.show(block=True);

Output:

Drawing a Horizontal Bar Chart for a pandas DataFrame in Python

Compound horizontal bar chart:

A compound horizontal bar chart is drawn for more than one variable. For each variable a horizontal bar is drawn in the corresponding category. The example Python code plots Inflation and Growth for each year as a compound horizontal bar chart.

Example:

# Example python program to plot a compound horizontal bar chart

# using pandas DataFrame

import pandas as pd

import matplotlib.pyplot as plot

 

# Python dictionary

inflationAndGrowth  = {"Growth rate": [7, 1.6, 1.5, 6.2],

                       "Inflation rate":[3.2, 3.4, 4.5, 2.7]};

index               = ["Country1", "Country2", "Country3", "Country4"];

 

# Python dictionary into a pandas DataFrame

dataFrame       = pd.DataFrame(data = inflationAndGrowth);

dataFrame.index = index;

 

dataFrame.plot.barh(rot=15, title="Inflation and Growth of different countries");

plot.show(block=True);

Output:

Compound Horizontal Bar Chart drawn for a pandas DataFrame in Python

Stacked horizontal bar chart:

A stacked horizontal bar chart, as the name suggests stacks one bar next to another in the X-axis. The significance of the stacked horizontal bar chart is, it helps depicting an existing part-to-whole relationship among multiple variables. The pandas example, plots horizontal bars for number of students appeared in an examination vis-a-vis the number of students who have passed the examination.

Example:

# Example Python program to plot a stacked horizontal bar chart 

import pandas as pd

import matplotlib.pyplot as plot

 

# A python dictionary

data = {"Appeared":[50000, 49000, 55000],

        "Passed":[4500, 5000, 4600]

        };

index     = ["2017", "2018", "2019"];

 

# Python Dictionary loaded into a DataFrame

dataFrame = pd.DataFrame(data=data, index=index);

 

# Draw a stacked horizontal bar chart

dataFrame.plot.barh(stacked=True,rot=-15, title="Number of students appeared vs passed");

plot.show(block=True);

Output:

Stacked Horizontal BarChart drawn using pandas DataFrame in Python


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