FPP Assignment No 14 and 15

Problem Statement:

Develop a program to create a DataFrame from a NumPy array with custom column names.

import numpy as np
import pandas as pd

# Create a NumPy array
data = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])

# Define custom column names
columns = ['Column A', 'Column B', 'Column C']

# Create a DataFrame
df = pd.DataFrame(data, columns=columns)

print("DataFrame created from NumPy array:")
print(df)

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2. Drawing a Bar Plot and Scatter Plot using Matplotlib

import matplotlib.pyplot as plt

# Data for plots
categories = ['A', 'B', 'C', 'D']
values = [4, 7, 1, 8]
x = [1, 2, 3, 4]
y = [10, 20, 25, 30]

# Bar Plot
plt.figure(figsize=(8, 4))
plt.bar(categories, values, color='skyblue')
plt.title("Bar Plot")
plt.xlabel("Categories")
plt.ylabel("Values")
plt.show()

# Scatter Plot
plt.figure(figsize=(8, 4))
plt.scatter(x, y, color='red', label='Points')
plt.title("Scatter Plot")
plt.xlabel("X-axis")
plt.ylabel("Y-axis")
plt.legend()
plt.show()

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Explanation:

1. DataFrame Creation:

   • The program uses np.array to create a data matrix.
   • Custom column names are passed to pd.DataFrame to create the DataFrame.

2. Bar Plot:

   • A bar plot is drawn using plt.bar, with labels for categories and values.

3. Scatter Plot:

   • A scatter plot is created using plt.scatter, with x and y as input points.

Let me know if you'd like to expand or modify these examples!