data-analysis

Name: data-analysis
Rating: 5 (2 reviews)
Author: bg-szy

Analyze datasets to extract insights, identify patterns, and generate reports. Use when exploring data, creating visualizations, or performing statistical analysis. Handles CSV, JSON, SQL queries, and Python pandas operations.

2stars

Updated last month

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#sql #python

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Data Analysis

When to use this skill

Data exploration: Understand a new dataset
Report generation: Derive data-driven insights
Quality validation: Check data consistency
Decision support: Make data-driven recommendations

Instructions

Step 1: Load and explore data

Python (Pandas):

import pandas as pd
import numpy as np

# Load CSV
df = pd.read_csv('data.csv')

# Basic info
print(df.info())
print(df.describe())
print(df.head(10))

# Check mis

[Description truncada. Veja o README completo no GitHub.]

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