How to Plot a DataFrame using Pandas

In this guide, you’ll see how to plot a DataFrame using Pandas, including:

• Scatter diagram
• Line chart
• Bar chart
• Pie chart

Plot a Scatter Diagram using Pandas

Step 1: Prepare the data

To start, prepare the data for your scatter diagram.

For example, the following data will be used to create the scatter diagram:

Step 2: Create the DataFrame

Next, create the DataFrame to capture the above data in Python:

import pandas as pd

data = {
    "unemployment_rate": [6.1, 5.8, 5.7, 5.7, 5.8, 5.6, 5.5, 5.3, 5.2, 5.2],
    "index_price": [1500, 1520, 1525, 1523, 1515, 1540, 1545, 1560, 1555, 1565],
}

df = pd.DataFrame(data)

print(df)

Run the code in Python, and you’ll get the following DataFrame:

   unemployment_rate  index_price
0                6.1         1500
1                5.8         1520
2                5.7         1525
3                5.7         1523
4                5.8         1515
5                5.6         1540
6                5.5         1545
7                5.3         1560
8                5.2         1555
9                5.2         1565

Step 3: Plot the DataFrame using Pandas

Finally, you can plot the DataFrame by adding the following syntax:

df.plot(x="unemployment_rate", y="index_price", kind="scatter")

Notice that you can specify the type of chart by setting kind=”scatter“.

You’ll also need to add the Matplotlib syntax to show the plot (ensure that the Matplotlib package is install in Python):

• import matplotlib.pyplot as plt
• plt.show()

Putting everything together:

import pandas as pd
import matplotlib.pyplot as plt

data = {
    "unemployment_rate": [6.1, 5.8, 5.7, 5.7, 5.8, 5.6, 5.5, 5.3, 5.2, 5.2],
    "index_price": [1500, 1520, 1525, 1523, 1515, 1540, 1545, 1560, 1555, 1565],
}

df = pd.DataFrame(data)

df.plot(x="unemployment_rate", y="index_price", kind="scatter")

plt.show()

Once you run the above code, you’ll get a scatter diagram.

Plot a Line Chart using Pandas

Step 1: Prepare the data

To start, prepare the data for the line chart:

Step 2: Create the DataFrame

Now create the DataFrame based on the above data:

import pandas as pd

data = {
    "year": [1920, 1930, 1940, 1950, 1960, 1970, 1980, 1990, 2000, 2010],
    "unemployment_rate": [9.8, 12, 8, 7.2, 6.9, 7, 6.5, 6.2, 5.5, 6.3],
}

df = pd.DataFrame(data)

print(df)

This is how the DataFrame would look like:

   year  unemployment_rate
0  1920                9.8
1  1930               12.0
2  1940                8.0
3  1950                7.2
4  1960                6.9
5  1970                7.0
6  1980                6.5
7  1990                6.2
8  2000                5.5
9  2010                6.3

Step 3: Plot the DataFrame using Pandas

Finally, plot the DataFrame by adding the following syntax:

df.plot(x="year", y="unemployment_rate", kind="line")

You’ll notice that the kind is now set to “line” in order to plot the line chart.

Here is the complete Python code:

import pandas as pd
import matplotlib.pyplot as plt

data = {
    "year": [1920, 1930, 1940, 1950, 1960, 1970, 1980, 1990, 2000, 2010],
    "unemployment_rate": [9.8, 12, 8, 7.2, 6.9, 7, 6.5, 6.2, 5.5, 6.3],
}

df = pd.DataFrame(data)

df.plot(x="year", y="unemployment_rate", kind="line")

plt.show()

And once you run the code, you’ll get a line chart.

Plot a Bar Chart using Pandas

Step 1: Prepare your data

Here, the following dataset will be used to create the bar chart:

Step 2: Create the DataFrame

Create the DataFrame as follows:

import pandas as pd
   
data = {'country': ['A', 'B', 'C', 'D', 'E'],
        'gdp_per_capita': [45000, 42000, 52000, 49000, 47000]
       }
  
df = pd.DataFrame(data)

print(df)

You’ll then get this DataFrame:

  country  gdp_per_capita
0       A           45000
1       B           42000
2       C           52000
3       D           49000
4       E           47000

Step 3: Plot the DataFrame using Pandas

Finally, add the following syntax to the Python code:

df.plot(x="country", y="gdp_per_capita", kind="bar")

In this case, set the kind=”bar” to plot the bar chart.

The complete Python code:

import pandas as pd
import matplotlib.pyplot as plt

data = {
    "country": ["A", "B", "C", "D", "E"],
    "gdp_per_capita": [45000, 42000, 52000, 49000, 47000],
}

df = pd.DataFrame(data)

df.plot(x="country", y="gdp_per_capita", kind="bar")

plt.show()

Run the code, and you’ll get a bar chart.

Plot a Pie Chart using Pandas

Step 1: Prepare your data

For demonstration purposes, the following data about the status of tasks is prepared:

Step 2: Create the DataFrame

You can then create the DataFrame using this code:

import pandas as pd

data = {"tasks": [300, 500, 700]}

df = pd.DataFrame(data, index=["tasks_pending", "tasks_ongoing", "tasks_completed"])

print(df)

You’ll now see this DataFrame:

                 tasks
tasks_pending      300
tasks_ongoing      500
tasks_completed    700

Step 3: Plot the DataFrame using Pandas

Finally, plot the DataFrame by adding the following syntax:

df.plot.pie(y="tasks", figsize=(5, 5), autopct="%1.1f%%", startangle=90)

And here is the complete Python code:

import pandas as pd
import matplotlib.pyplot as plt

data = {"tasks": [300, 500, 700]}

df = pd.DataFrame(data, index=["tasks_pending", "tasks_ongoing", "tasks_completed"])

df.plot.pie(y="tasks", figsize=(5, 5), autopct="%1.1f%%", startangle=90)

plt.show()

Once you run the code, you’ll get a pie chart.

You just reviewed few examples about plotting DataFrames using Pandas. A good additional source for plotting DataFrames is the Pandas Documentation.