PYTHON DATA VISULATION By any CSV file by Sandeep Singh

📊 Python Data Viz · MCA Lab (fixed)

⏳ loading Pyodide... 📁 Upload CSV

✎ Python editor (pandas, matplotlib, numpy, sklearn) dataset as 'df'

import pandas as pd import matplotlib.pyplot as plt import numpy as np # 'df' is automatically loaded from uploaded CSV (or default iris) print("Data shape:", df.shape) print("Columns:", list(df.columns)) # Simple scatter plot (first two numeric columns) numeric_cols = df.select_dtypes(include=[np.number]).columns[:2] if len(numeric_cols) >= 2: plt.figure(figsize=(6,4)) plt.scatter(df[numeric_cols[0]], df[numeric_cols[1]]) plt.xlabel(numeric_cols[0]) plt.ylabel(numeric_cols[1]) plt.title("Scatter plot") plt.tight_layout() plt.show() else: print("Not enough numeric columns for scatter.")

📄 Default dataset: Iris (150 rows, 5 cols)

📚 Quick snippets

Line plot
plt.plot(df['col1'])

Histogram
df['col'].hist()

Bar chart
df['cat'].value_counts().plot(kind='bar')

Box plot
df.boxplot(column='num')

Correlation
df.corr()

Head/Tail
df.head() / df.tail()

📋 output & visualization ⏱️ -

⏳ initializing Python environment...