Problem occurs while preparing report from R script

[Imran79]

Hello Everyone
this is imran iam completing the Google Data Analytics Certificate course in my last course i have to do the capstone project iam almost completed the project but at the last i got the error when
compile the report i dont know how to correct tha please someone help me to get this problem right and also oi attach the screenshot about the problem

Thank You

[startz]

You need to load libraries inside the .RMD file. Markdown runs in a separate environment from the console.

[Imran79]

Thankyou for your answer sir but it did not work and i already load my libriarys in my rmd file sir please suggest me any other solutions for my problem

[startz]

Post some or all of the rmd file, something just large enough to cause the error. Post it as text, not as a picture.

[Imran79]

hii sir here is my full code

jan <- read_csv("202101-divvy-tripdata.csv")
feb <- read_csv("202102-divvy-tripdata.csv")
mar<- read_csv("202103-divvy-tripdata.csv")
apr <- read_csv("202104-divvy-tripdata.csv")
may <- read_csv("202105-divvy-tripdata.csv")
jun <- read_csv("202106-divvy-tripdata.csv")
jul <- read_csv("202107-divvy-tripdata.csv")
aug <- read_csv("202108-divvy-tripdata.csv")
sep <- read_csv("202109-divvy-tripdata.csv")
oct <- read_csv("202110-divvy-tripdata.csv")
nov <- read_csv("202111-divvy-tripdata.csv")
dec <- read_csv("202112-divvy-tripdata.csv")
library(readr)
library(pandoc)
library(rmarkdown)
library(ggplot2)

#----------Check column names for consistency
colnames(jan)
colnames(feb)
colnames(mar)
colnames(apr)
colnames(may)
colnames(jun)
colnames(jul)
colnames(aug)
colnames(sep)
colnames(oct)
colnames(nov)
colnames(dec)

#----------Merge monthly data into quarterly collection
q1_df <- rbind (jan, feb, mar)
q2_df <- rbind (apr, may, jun)
q3_df <- rbind (jul, aug, sep)
q4_df <- rbind (oct, nov, dec)
full_df <- rbind(jan,feb,mar,apr,may,jun,jul,aug,sep,oct,nov,dec)

#----------Remove monthly data to clear environment
remove(jan,feb,mar,apr,may,jun,jul,aug,sep,oct,nov,dec)

#----------Inspect dataframes and look for incongruencies
str(q1_df)
str(q2_df)
str(q3_df)
str(q4_df)
str(full_df)

#----------Remove rows with missing data
q1_df <- na.omit(q1_df)
q2_df <- na.omit(q2_df)
q3_df <- na.omit(q3_df)
q4_df <- na.omit(q4_df)
full_df <- na.omit(full_df)

#----------Convert trip_duration to numeric to calculate correctly
q1_df <- mutate(q1_df, trip_duration=as.numeric(trip_duration))
q2_df <- mutate(q2_df, trip_duration=as.numeric(trip_duration))
q3_df <- mutate(q3_df, trip_duration=as.numeric(trip_duration))
q4_df <- mutate(q4_df, trip_duration=as.numeric(trip_duration))
full_df <- mutate(full_df, trip_duration2=as.numeric(trip_duration))

#----------Full year data frame, clear quarterly data
full_df <- rbind(q1_df, q2_df, q3_df, q4_df)
remove(q1_df, q2_df, q3_df, q4_df)

#---------------Plots

#----------Total rides per year by member/casual
full_df %>%
group_by(member_casual) %>%
summarise(number_of_rides = n()) %>%
arrange(member_casual) %>%
ggplot(aes(x = member_casual,
y = number_of_rides,
fill = member_casual)) +
labs(fill='Rider Group') +
geom_col(position = "dodge") +
ggtitle(label = 'Total Rides per Year', subtitle = 'Casual Riders vs Members') +
theme(plot.title = element_text(hjust = 0.5)) +
theme(plot.subtitle = element_text(hjust = 0.5)) +
xlab('Rider Group') + ylab('Number of Rides') +
geom_text(aes(label = number_of_rides), vjust = 0)

#----------Rides per month by member/casual
full_df$month <- ordered(full_df$month, levels=c("January", "February", "March", "April", "May", "June", "July", "August", "September", "October", "November", "December")) #rearrange months to January -> December
full_df %>%
group_by(member_casual, month) %>%
summarise(number_of_rides = n()) %>%
arrange(member_casual, month) %>%
ggplot(aes(x = month,
y = number_of_rides,
fill = member_casual)) +
labs(fill='Rider Group') +
geom_col(position = "dodge") +
ggtitle(label = 'Total Rides per Month', subtitle = 'Casual Riders vs Members') +
theme(plot.title = element_text(hjust = 0.5)) +
theme(plot.subtitle = element_text(hjust = 0.5)) +
xlab('Month') + ylab('Number of Rides') +
geom_text(aes(label = number_of_rides, hjust = "left"), position = position_dodge(width = 0.9),size = 3, angle = 90)

#----------Rides per day by member/casual
full_df$week_days <- ordered(full_df$week_days, levels=c("Monday", "Tuesday", "Wednesday", "Thursday", "Friday", "Saturday", "Sunday")) #rearrange weekdays to monday -> sunday
full_df %>%
group_by(member_casual, week_days) %>%
summarise(number_of_rides = n()) %>%
arrange(member_casual, week_days) %>%
ggplot(aes(x = week_days,
y = number_of_rides,
fill = member_casual)) +
labs(fill='Rider Group') +
geom_col(position = "dodge") +
ggtitle(label = 'Total Rides per Day', subtitle = 'Casual Riders vs Members') +
theme(plot.title = element_text(hjust = 0.5)) +
theme(plot.subtitle = element_text(hjust = 0.5)) +
xlab('Day of Week') + ylab('Number of Rides') +
geom_text(aes(label = number_of_rides, hjust = "right"), position = position_dodge(width = 0.9),size = 3, angle = 90)

#----------Average trip duration by member/casual
full_df %>%
group_by(member_casual) %>%
summarise(average_duration = mean(trip_duration)) %>%
arrange(member_casual) %>%
ggplot(aes(x = member_casual,
y = average_duration/60,
fill = member_casual)) +
labs(fill='Rider Group') +
geom_col(position = "dodge") +
ggtitle(label = 'Average Trip Duration', subtitle = 'Casual Riders vs Members') +
theme(plot.title = element_text(hjust = 0.5)) +
theme(plot.subtitle = element_text(hjust = 0.5)) +
xlab('Rider Group') + ylab('Trip Duration in Minutes') +
geom_text(aes(label = round(average_duration/60, digits = 2)), vjust = 0)

#----------Average trip duration per month by member/casual
full_df %>%
group_by(member_casual, month) %>%
summarise(average_duration = mean(trip_duration)) %>%
arrange(member_casual, month) %>%
ggplot(aes(x = month,
y = average_duration/60,
fill = member_casual)) +
labs(fill='Rider Group') +
geom_col(position = "dodge") +
ggtitle(label = 'Average Trip Duration by Month', subtitle = 'Casual Riders vs Members') +
theme(plot.title = element_text(hjust = 0.5)) +
theme(plot.subtitle = element_text(hjust = 0.5)) +
xlab('Month') + ylab('Trip Duration in Minutes') +
geom_text(aes(label = round(average_duration/60, digits = 2), hjust = "right"), position = position_dodge(width = 0.9),size = 3, angle = 90)

#----------Average trip duration per weekday by member/casual
full_df %>%
group_by(member_casual, week_days) %>%
summarise(average_duration = mean(trip_duration)) %>%
arrange(member_casual, week_days) %>%
ggplot(aes(x = week_days,
y = average_duration/60,
fill = member_casual)) +
labs(fill='Rider Group') +
geom_col(position = "dodge") +
ggtitle(label = 'Average Trip Duration by Weekday', subtitle = 'Casual Riders vs Members') +
theme(plot.title = element_text(hjust = 0.5)) +
theme(plot.subtitle = element_text(hjust = 0.5)) +
xlab('Day of Week') + ylab('Trip Duration in Minutes') +
geom_text(aes(label = round(average_duration/60, digits = 2), hjust = "right"), position = position_dodge(width = 0.9),size = 3, angle = 90)

#----------Bike Preference per Rider Group
full_df %>%
group_by(member_casual, rideable_type) %>%
summarise(number_of_rides = n()) %>%
arrange(member_casual, rideable_type) %>%
ggplot(aes(x = rideable_type,
y = number_of_rides,
fill = member_casual)) +
labs(fill='Rider Group') +
geom_col(position = "dodge") +
ggtitle(label = 'Total Rides per Year by Bike Type', subtitle = 'Casual Riders vs Members') +
theme(plot.title = element_text(hjust = 0.5)) +
theme(plot.subtitle = element_text(hjust = 0.5)) +
xlab('Bike Type') + ylab('Number of Rides') +
geom_text(aes(label = number_of_rides), position = position_dodge(width = 0.9), vjust = 0)

#----------Average trip duration per bike type
full_df %>%
group_by(member_casual, rideable_type) %>%
summarise(average_duration = mean(trip_duration)) %>%
arrange(member_casual, rideable_type) %>%
ggplot(aes(x = rideable_type,
y = average_duration/60,
fill = member_casual)) +
labs(fill='Rider Group') +
geom_col(position = "dodge") +
ggtitle(label = 'Average Trip Duration by Bike Type', subtitle = 'Casual Riders vs Members') +
theme(plot.title = element_text(hjust = 0.5)) +
theme(plot.subtitle = element_text(hjust = 0.5)) +
xlab('Bike Type') + ylab('Trip Duration in Minutes') +
geom_text(aes(label = round(average_duration/60, digits = 2)), position = position_dodge(width = 0.9), vjust = 0)

[startz]

The library command has to come before using the functions

[Imran79]

Thank You sir its working but please tell me how to publish it with our own text like the link i given below

this link is how i want to publish
https://rpubs.com/JAlves96/1015155

but when i publish it will shows only my code and result of my code and in don't know how to add my own text to make my publish better please help me sir

Thank You

[startz]

R Markdown is a language of it's own. You write text and headers and such outside of the R code chunks. RStudio has a link to R Markdown cheatsheets. Or take a look at R Markdown Cookbook.

[Imran79]

okk sir very Thank You