app.py
|
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 |
import pandas as pd import seaborn as sns import matplotlib.pyplot as plt import os # Load CSV data into a DataFrame df = pd.read_csv("data.csv") # Create output directory os.makedirs('output_seaborn_charts', exist_ok=True) # 1. Bar Plot plt.figure(figsize=(8, 5)) sns.barplot(x="name", y="age", data=df, palette="pastel") plt.title("Bar Plot: User Ages") plt.tight_layout() plt.savefig("output_seaborn_charts/bar_plot.png") plt.savefig("output_seaborn_charts/bar_plot.pdf") plt.close() # 2. Line Plot plt.figure(figsize=(8, 5)) sns.lineplot(x="name", y="age", data=df, marker="o", linestyle="-", color="green") plt.title("Line Plot: User Ages") plt.tight_layout() plt.savefig("output_seaborn_charts/line_plot.png") plt.savefig("output_seaborn_charts/line_plot.pdf") plt.close() # 3. Strip Plot (Categorical scatter plot) plt.figure(figsize=(8, 5)) sns.stripplot(x="name", y="age", data=df, jitter=True, size=8, palette="Set2") plt.title("Strip Plot: User Ages") plt.tight_layout() plt.savefig("output_seaborn_charts/strip_plot.png") plt.savefig("output_seaborn_charts/strip_plot.pdf") plt.close() print("Seaborn charts created and saved in 'output_seaborn_charts' folder.") |
