import os
import pandas as pd
import matplotlib.pyplot as plt
# Get the filepath to the data file.
filepath = os.path.join(os.getcwd(), 'data', 'iris.csv')
# Read the data file into a Pandas DataFrame.
df = pd.read_csv(filepath)
# Plot the data.
plt.scatter(df['petal_length'], df['petal_width'])
plt.xlabel('Petal Length')
plt.ylabel('Petal Width')
plt.title('Iris Data Scatter Plot')
plt.show()
```The provided Python code demonstrates data visualization using Matplotlib and Pandas libraries to plot a scatter plot of petal length and petal width data from the iris dataset. A brief explanation of the code below:
1. Import essential libraries:
- `os`: Used for file path manipulation.
- `pandas as pd`: Used for data manipulation and reading CSV files.
- `matplotlib.pyplot as plt`: Used for data visualization.
2. Obtain the filepath to the iris dataset CSV file:
- `filepath`: The file path is constructed by joining the current working directory, a subdirectory named 'data,' and the filename 'iris.csv.'
3. Read the CSV file into a Pandas DataFrame:
- `df`: Pandas reads the CSV file into a DataFrame named 'df.' Each column in the CSV file becomes a column in the DataFrame.
4. Create a scatter plot using Matplotlib:
- `plt.scatter(df['petal_length'], df['petal_width'])`: Creates a scatter plot using the 'petal_length' column as the x-axis values and the 'petal_width' column as the y-axis values. Each data point is represented as a circle on the plot.
5. Add labels and a title to the plot:
- `plt.xlabel('Petal Length')`: Sets the label for the x-axis as 'Petal Length.'
- `plt.ylabel('Petal Width')`: Sets the label for the y-axis as 'Petal Width.'
- `plt.title('Iris Data Scatter Plot')`: Sets the title of the plot as 'Iris Data Scatter Plot.'
6. Display the plot:
- `plt.show()`: Displays the scatter plot on the screen.
When you run this code, it will read the iris dataset from the specified CSV file, plot a scatter plot of petal length versus petal width, and display it with appropriate labels and a title. This visualization helps visualize the relationship between these two petal characteristics in the iris dataset.
In summary, this code uses the Pandas library to read data from a CSV file and the Matplotlib library to visualize that data as a scatter plot. It's a simple yet effective way to explore and visualize data in Python.
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