Exploratory Analysis
Discover patterns, relationships, and insights in your data
What is Exploratory Data Analysis?
Exploratory Data Analysis (EDA) is an approach to analyzing data sets to summarize their main characteristics, often using visual methods. It helps identify patterns, spot anomalies, test hypotheses, and check assumptions.
The EDA Process
Data Understanding
Examine data structure and content
Pattern Discovery
Identify trends and relationships
Insight Generation
Draw conclusions and hypotheses
Visualization Techniques
Univariate Analysis
- • Histograms
- • Box plots
- • Density plots
- • Bar charts
Multivariate Analysis
- • Scatter plots
- • Correlation matrices
- • Pair plots
- • Heat maps
Implementation Example
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
import numpy as np
# Load data
df = pd.read_csv('dataset.csv')
# Basic data exploration
print("Dataset Info:")
print(df.info())
print("
Summary Statistics:")
print(df.describe())
# Univariate analysis
plt.figure(figsize=(12, 6))
sns.histplot(data=df, x='numeric_column', kde=True)
plt.title('Distribution of Numeric Column')
plt.show()
# Box plot for outlier detection
plt.figure(figsize=(10, 6))
sns.boxplot(data=df, x='category', y='numeric_column')
plt.title('Box Plot by Category')
plt.show()
# Correlation analysis
plt.figure(figsize=(10, 8))
correlation_matrix = df.corr()
sns.heatmap(correlation_matrix, annot=True, cmap='coolwarm')
plt.title('Correlation Matrix')
plt.show()
# Pair plot for multiple variables
sns.pairplot(data=df, hue='category')
plt.suptitle('Pair Plot of Variables')
plt.show()
# Time series analysis (if applicable)
if 'date' in df.columns:
df['date'] = pd.to_datetime(df['date'])
plt.figure(figsize=(15, 6))
sns.lineplot(data=df, x='date', y='value')
plt.title('Time Series Plot')
plt.show()Analysis Checklist
Data Quality Checks
- • Check for missing values
- • Identify outliers
- • Examine data types
- • Verify data ranges
Pattern Analysis
- • Look for trends
- • Identify correlations
- • Examine distributions
- • Study group differences