Key-findings.Rmd

---
title: "Cyclistic 2023 | Key findings"
author: "Lucio Colonna"
date: "`r paste('<br>Last updated: ',format(Sys.Date(), '%A %B %d, %Y'),'')`"
output: 
  github_document
editor_options: 
  markdown: 
    wrap: 72
---

```{r global options, include=FALSE}
knitr::opts_chunk$set(tidy.opts = list(width.cutoff = 60), tidy = TRUE)
```

<br>

## Key findings

📌 **User Composition and Ride Patterns** 🚴‍♀️

- Members account for a **larger proportion** of total rides (**65%**) compared to casual (**35%**)
- Members prefer more **frequent** and **short rides**, while casual users take longer trips

---

📌 **Trip Duration and Frequency** ⏱️

- Casual users collectively spend **more time on bikes** due to longer trip durations (average duration of **23.2 minutes**), while members use the service more efficiently for shorter, more frequent trips (average duration of **12.4 minutes**)
- **50%** of all rides last **10 minutes or less**, with casual users’ median duration at **13.00 minutes** and members’ at **8.78 minutes**
- The vast majority of rides (**97%**) last **less than 60 minutes**
- Both groups demonstrate a significant **decline** in trip counts after **5 minutes** for members and **7 minutes** for casual users, indicating a preference for shorter travel durations

---

📌 **Round Trips** 🔄

- Casual users make more **round trips** (**8%**) than members (**3%**), indicating **leisure usage**
- Casual users’ average round trip duration is **44.24 minutes**, compared to members’ **23.31 minutes**

---

📌 **Trip Distance** 📏

- Approximately 99% of trips are **less than 10 km** (excluding round trips which have a distance of 0, otherwise it would be **95%**). Specifically, **60%** of rides are **up to 2 km**, and **~92%** are **up to 5 km**
- Both groups show a steep **decline** in trip counts **beyond 2 km**, reinforcing a preference for short-distance travel

---

📌 **Seasonal and Temporal Variations** ☀️

- Both user groups show increased activity in **warmer months**, with **peaks in the third quarter** and lowest ride counts in the first and fourth quarters
- There is a strong positive correlation with **average temperatures**, indicating that better weather conditions significantly boost bike usage
- There is a **strong positive correlation** between monthly ride counts and average ride duration for both user groups, suggesting that as the number of rides per month increases, so does the average duration of those rides

---

📌 **Weekdays vs Weekends** 📅

- Members predominantly use bikes on **weekdays** (**77%**), likely for commuting, while casual users have slightly more balanced usage between weekdays (**63%**) and weekends (**37%**)

---

📌 **Hour of Day** ⏰

- Ride counts for casual users gradually **increase throughout the day**, peaking around **5 PM**. Their ride counts are relatively steady during the late morning and early afternoon hours, indicating a **consistent** use pattern.
- Members show distinct **peak** in ride counts during the **morning commute** (7 AM to 9 AM) and the **evening commute** (4 PM to 6 PM). This reflects their use of the service for **work-related travel**. The rides count **drops** significantly during **mid-day** and **late evening hours**

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📌 **Bike Preferences** 🚲

- Both groups prefer **classic bikes**, with a slightly stronger preference among members (**65%**) than casual users (**62%**)
- Electric bikes are used for **longer trips** and are more popular on **weekdays**
- Members on average **ride both types of bikes faster** than casual users, indicating more **efficient usage**

---

📌 **Geographic Usage** 🗺️

- Downtown Chicago, particularly the **Loop**, **Gold Coast**, **Near South Side**, and **Navy Pier**, sees the **highest ride counts**. Moderate-density areas include **Lincoln Park**, **Lakeview**, **South Loop**, **Logan Square**, and **Irvin Park**. Low-density areas, such as **Norridge** and **Summit**, have the lowest ride counts
- Casual users are **concentrated in downtown and southern neighborhoods**, primarily around **tourist attractions**
- Member usage is more **dispersed across the city**, with higher activity in **northern and central regions**, indicating regular commuting patterns

---

📌 **Popular Routes and Stations** 📍

- Casual users favor **round trips around tourist areas**, while members use the service for **point-to-point travel**, emphasizing commuting and daily activities
- **A small number of stations** significantly contribute to overall ride volume, especially for casual users