Exploring My Data

My First Test

1. Introduction

In this post I explore traffic data and visualize hourly trendlines.

2. Load the data

```python import pandas as pd df = pd.read_csv(“data/traffic.csv”, parse_dates=[“timestamp”]) df[“hour”] = df[“timestamp”].dt.hour hours = df.groupby(“hour”)[“count”].mean() print(hours.head())

```r library(forecast) fit <- auto.arima(hours) forecast(fit, h = 24)

– This structure gives headers, code, a static image graph, inline captions, etc.

4. 📊 Adding Graphs (Static vs Interactive)

Option A: Static graph (easiest)

1. Compute or train your graph in Python/R.
2. Save it as a .png or .svg into e.g. /assets/plots/average.png.
3. Reference in Markdown using:

```markdown