Created
August 10, 2024 05:40
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| library(tidyverse) | |
| library(dplyr) | |
| library(tibble) | |
| library(janitor) | |
| library("lubridate") | |
| library(here) | |
| library(skimr) | |
| library(ggplot2) | |
| #READ CSV FILES | |
| #------------------------------------------------------------------------------- | |
| date_format <- r"{%Y-%m-%d %H:%M:%s}" | |
| setwd(r"{C:\Users\marti\Desktop\data analysis\case_study\data}") | |
| csv_locations <- r"{C:\Users\marti\Desktop\data analysis\case_study\data}" | |
| cyclistic_file <- list.files(path=csv_locations, pattern = "\\.csv$",full.names = TRUE) | |
| bike_share_data <- read_csv(cyclistic_file) | |
| #------------------------------------------------------------------------------- | |
| count(bike_share_data2) | |
| #CLEAN DATE FORMAT | |
| #------------------------------------------------------------------------------- | |
| bike_share_cleaned <- bike_share_data %>% | |
| mutate(started_at = case_when( | |
| is.na(as_date(started_at,"{%Y-%m-%d %H:%M:%s}")) ~ mdy_hms(started_at), | |
| TRUE ~ as_datetime(started_at))) %>% | |
| mutate(ended_at = case_when( | |
| is.na(as_date(ended_at,"{%Y-%m-%d %H:%M:%s}")) ~ mdy_hms(ended_at), | |
| TRUE ~ as_datetime(ended_at))) | |
| #------------------------------------------------------------------------------- | |
| #CLEAN STARTED_AT>ENDED_AT | |
| #------------------------------------------------------------------------------- | |
| bike_share_cleaned <- bike_share_cleaned %>% | |
| filter(started_at<ended_at) | |
| #------------------------------------------------------------------------------- | |
| # columns added for analysis | |
| #------------------------------------------------------------------------------- | |
| bike_share_cleaned <- bike_share_cleaned %>% | |
| mutate(ride_length = as.numeric(difftime(ended_at,started_at)/60)) | |
| #------------------------------------------------------------------------------- | |
| quant_no_outliers <- quantile(bike_share_cleaned$ride_length, seq (0,0.999,by=0.001)) | |
| test_quantile <- bike_share_cleaned %>% filter(ride_length < as.numeric(quant_no_outliers['99.9%'])) | |
| ggplot(test_quantile,aes(x =started_at,y = ride_length))+geom_line() |
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