How to Create a Stacked Bar Chart in Pandas with Grouped Data?

Plotting a Stacked Bar Chart Using Pandas

Question:

How can I create a stacked bar chart with pandas, similar to the image provided? My current dataframe consists of separate columns for "Site Name" and "Abuse/NFF" counts, and I'm unable to arrange the data or generate the stacked bar chart.

Solution:

1. Data Preparation:

Create a new dataframe by grouping the data by both "Site Name" and "Abuse/NFF" and counting the occurrences of each combination.

2. Stacking the Data:

Use the .unstack() method to create a stacked dataframe, with "Site Name" as the index and "Abuse/NFF" as the columns.

3. Filling Missing Values:

Handle any missing values by filling them with zeros using the .fillna(0) method.

4. Plotting the Bar Chart:

Use the .plot() method with the kind parameter set to 'bar' and the stacked parameter set to True to generate a stacked bar chart.

Python Code:

<code class="python">import pandas as pd
import matplotlib.pyplot as plt

# Create a dataframe from the CSV file
df = pd.read_csv("data.csv")

# Group by "Site Name" and "Abuse/NFF" and count occurrences
df2 = df.groupby(['Site Name', 'Abuse/NFF'])['Site Name'].count().unstack('Abuse/NFF').fillna(0)

# Plot the stacked bar chart
df2[['abuse','nff']].plot(kind='bar', stacked=True)
plt.show()</code>

Output:

The resulting plot will resemble the image provided in the original question, displaying the stacked counts of "Abuse" and "NFF" for each "Site Name."

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