Python data visualization examples

Python data visualization examples

Here are some Python data visualization examples using popular libraries like Matplotlib and Seaborn:

import matplotlib.pyplot as plt
import numpy as np
x = np.arange(0, 10, 0.1)
y = np.sin(x)
plt.plot(x, y)
plt.xlabel('X Axis')
plt.ylabel('Y Axis')
plt.title('Sine Wave')
plt.show()

This code generates a simple line plot showing the sine wave function.

import matplotlib.pyplot as plt
fruits = ['Apple', 'Banana', 'Cherry']
counts = [3, 5, 2]
plt.bar(fruits, counts)
plt.xlabel('Fruit')
plt.ylabel('Count')
plt.title('Fruit Counts')
plt.show()

This code creates a bar chart showing the count of different fruits.

import matplotlib.pyplot as plt
import numpy as np
data = np.random.normal(0, 1, 1000)
plt.hist(data, bins=30)
plt.xlabel('Value')
plt.ylabel('Frequency')
plt.title('Histogram of Random Data')
plt.show()

This code generates a histogram showing the distribution of random data.

import matplotlib.pyplot as plt
import numpy as np
x = np.random.normal(0, 1, 100)
y = np.random.normal(0, 1, 100)
plt.scatter(x, y)
plt.xlabel('X Axis')
plt.ylabel('Y Axis')
plt.title('Scatter Plot of Random Data')
plt.show()

This code creates a scatter plot showing the relationship between two sets of random data.

import seaborn as sns
import matplotlib.pyplot as plt
tips = sns.load_dataset('tips')
sns.set()
sns.heatmap(tips.corr(), annot=True, cmap='coolwarm', square=True)
plt.title('Correlation Matrix')
plt.show()

This code generates a heatmap showing the correlation matrix of the tips dataset.

import seaborn as sns
import matplotlib.pyplot as plt
tips = sns.load_dataset('tips')
sns.set()
sns.boxplot(x='day', y='total_bill', data=tips)
plt.title('Total Bill by Day')
plt.show()

This code creates a box plot showing the distribution of total bill amounts by day.

import matplotlib.pyplot as plt
fruits = ['Apple', 'Banana', 'Cherry']
counts = [3, 5, 2]
plt.pie(counts, labels=fruits, autopct='%1.1f%%')
plt.title('Fruit Counts')
plt.show()

This code generates a pie chart showing the count of different fruits.

These are just a few examples of the many types of data visualizations you can create with Python and popular libraries like Matplotlib and Seaborn.

Can you visualize data in Python?

I'd be happy to help!

Yes, Python provides various ways to visualize data, making it a powerful tool for data analysis and visualization. Here are some popular methods:

Here's an example code snippet using Matplotlib:

import matplotlib.pyplot as plt
x = [1, 2, 3, 4, 5]
y = [2, 4, 6, 8, 10]
plt.plot(x, y)
plt.xlabel('X Axis')
plt.ylabel('Y Axis')
plt.title('Line Plot Example')
plt.show()

This code creates a simple line plot with x and y coordinates. You can customize the appearance of the plot by adding more lines, changing colors, fonts, labels, and other attributes.

In addition to these libraries, Python also provides built-in functions for creating visualizations, such as:

These are just a few examples of the many ways you can visualize data in Python. The choice of library often depends on your specific use case, personal preference, and the type of visualization you want to create.