Mixing
Compare 2 data frames with ggplot
0
I have the below dataframes and want to plot 2 weeks of data with ggplot.
df<-data.frame(
Date=sample(seq(as.Date('2018-10-25'), as.Date('2018-11-20'), by = "day"), 100,replace = T),
category1=sample(letters[1:6],100,replace = T),
count=sample(1:1000,100,replace = T)
)
Data Frame-1 (Last 7 Days)
df1<-df%>%select(everything())%>%filter(Date < Sys.Date()-1 & Date>=Sys.Date()-8)%>%
group_by(Date,category1)%>%summarise(Total=sum(count))
Data Frame-2 (Last 8 days to 15 days)
df2<-df%>%select(everything())%>%filter(Date < Sys.Date()-8 & Date>=Sys.Date()-15)%>%
group_by(Date,category1)%>%summarise(Total=sum(count))
Plots :
ggplot(df1,aes(Date,Total,fill=category1))+geom_bar(stat = "identity",position = "stack",width = 0.8,alpha=0.8)
ggplot(df2,aes(Date,Total,fill=category1))+geom_bar(stat = "identity",position = "stack",width = 0.8,alpha=0.8)
Now how to plot the same content comparing the 2 plots ?
Any extra information if required please let me know.
r ggplot2
asked Nov 20 '18 at 4:01
sai saransai saran
348224
add a comment |
0
I have the below dataframes and want to plot 2 weeks of data with ggplot.
df<-data.frame(
Date=sample(seq(as.Date('2018-10-25'), as.Date('2018-11-20'), by = "day"), 100,replace = T),
category1=sample(letters[1:6],100,replace = T),
count=sample(1:1000,100,replace = T)
)
Data Frame-1 (Last 7 Days)
df1<-df%>%select(everything())%>%filter(Date < Sys.Date()-1 & Date>=Sys.Date()-8)%>%
group_by(Date,category1)%>%summarise(Total=sum(count))
Data Frame-2 (Last 8 days to 15 days)
df2<-df%>%select(everything())%>%filter(Date < Sys.Date()-8 & Date>=Sys.Date()-15)%>%
group_by(Date,category1)%>%summarise(Total=sum(count))
Plots :
ggplot(df1,aes(Date,Total,fill=category1))+geom_bar(stat = "identity",position = "stack",width = 0.8,alpha=0.8)
ggplot(df2,aes(Date,Total,fill=category1))+geom_bar(stat = "identity",position = "stack",width = 0.8,alpha=0.8)
Now how to plot the same content comparing the 2 plots ?
Any extra information if required please let me know.
r ggplot2
asked Nov 20 '18 at 4:01
sai saransai saran
348224
i want to compare first data frame result with second data frame result like TOTAL count needs to be compare with one week to another week
– sai saran
Nov 20 '18 at 4:14
to know how the progress of total from one week to last week data
– sai saran
Nov 20 '18 at 4:14
add a comment |
0
0
0
I have the below dataframes and want to plot 2 weeks of data with ggplot.
df<-data.frame(
Date=sample(seq(as.Date('2018-10-25'), as.Date('2018-11-20'), by = "day"), 100,replace = T),
category1=sample(letters[1:6],100,replace = T),
count=sample(1:1000,100,replace = T)
)
Data Frame-1 (Last 7 Days)
df1<-df%>%select(everything())%>%filter(Date < Sys.Date()-1 & Date>=Sys.Date()-8)%>%
group_by(Date,category1)%>%summarise(Total=sum(count))
Data Frame-2 (Last 8 days to 15 days)
df2<-df%>%select(everything())%>%filter(Date < Sys.Date()-8 & Date>=Sys.Date()-15)%>%
group_by(Date,category1)%>%summarise(Total=sum(count))
Plots :
ggplot(df1,aes(Date,Total,fill=category1))+geom_bar(stat = "identity",position = "stack",width = 0.8,alpha=0.8)
ggplot(df2,aes(Date,Total,fill=category1))+geom_bar(stat = "identity",position = "stack",width = 0.8,alpha=0.8)
Now how to plot the same content comparing the 2 plots ?
Any extra information if required please let me know.
r ggplot2
asked Nov 20 '18 at 4:01
sai saransai saran
348224
I have the below dataframes and want to plot 2 weeks of data with ggplot.
df<-data.frame(
Date=sample(seq(as.Date('2018-10-25'), as.Date('2018-11-20'), by = "day"), 100,replace = T),
category1=sample(letters[1:6],100,replace = T),
count=sample(1:1000,100,replace = T)
)
Data Frame-1 (Last 7 Days)
df1<-df%>%select(everything())%>%filter(Date < Sys.Date()-1 & Date>=Sys.Date()-8)%>%
group_by(Date,category1)%>%summarise(Total=sum(count))
Data Frame-2 (Last 8 days to 15 days)
df2<-df%>%select(everything())%>%filter(Date < Sys.Date()-8 & Date>=Sys.Date()-15)%>%
group_by(Date,category1)%>%summarise(Total=sum(count))
Plots :
ggplot(df1,aes(Date,Total,fill=category1))+geom_bar(stat = "identity",position = "stack",width = 0.8,alpha=0.8)
ggplot(df2,aes(Date,Total,fill=category1))+geom_bar(stat = "identity",position = "stack",width = 0.8,alpha=0.8)
Now how to plot the same content comparing the 2 plots ?
Any extra information if required please let me know.
r ggplot2
r ggplot2
asked Nov 20 '18 at 4:01
sai saransai saran
348224
asked Nov 20 '18 at 4:01
sai saransai saran
348224
asked Nov 20 '18 at 4:01
sai saransai saran
348224
asked Nov 20 '18 at 4:01
sai saransai saran
348224
asked Nov 20 '18 at 4:01
sai saransai saran
348224
348224
i want to compare first data frame result with second data frame result like TOTAL count needs to be compare with one week to another week
– sai saran
Nov 20 '18 at 4:14
to know how the progress of total from one week to last week data
– sai saran
Nov 20 '18 at 4:14
add a comment |
i want to compare first data frame result with second data frame result like TOTAL count needs to be compare with one week to another week
– sai saran
Nov 20 '18 at 4:14
to know how the progress of total from one week to last week data
– sai saran
Nov 20 '18 at 4:14
i want to compare first data frame result with second data frame result like TOTAL count needs to be compare with one week to another week
– sai saran
Nov 20 '18 at 4:14
i want to compare first data frame result with second data frame result like TOTAL count needs to be compare with one week to another week
– sai saran
Nov 20 '18 at 4:14
to know how the progress of total from one week to last week data
– sai saran
Nov 20 '18 at 4:14
to know how the progress of total from one week to last week data
– sai saran
Nov 20 '18 at 4:14
add a comment |
1 Answer
1
active
oldest
votes
2
Here's an approach using facets, where I show each date of the last week as a facet, with the # of whole weeks prior on the x axis of each facet.
library(tidyverse)
df1 <- df %>%
mutate(days_old = (as.Date("2018-11-20") - Date) / lubridate::ddays(1),
weeks_ago = days_old %/% 7,
adj_to_this_week = as.Date("2018-11-20") - days_old %% 7) %>%
group_by(adj_to_this_week, weeks_ago, category1) %>%
summarise(Total=sum(count))
ggplot(df1 %>%
filter(weeks_ago <= 1) %>%
mutate(nice_dates = format(adj_to_this_week, "%b %d") %>%
fct_reorder(adj_to_this_wk)),
aes(-weeks_ago, Total,fill=category1)) +
geom_bar(stat = "identity",position = "stack",width = 0.8,alpha=0.8) +
scale_x_continuous(breaks = -1:0, labels = c("LW", "TW")) +
facet_wrap(~nice_dates, nrow = 1) +
labs(title = "Last week (LW) vs. This week (TW)", x ="") +
theme(panel.grid.major.x = element_blank(),
panel.grid.minor.x = element_blank())
Sample data:
set.seed(42)
df<-data.frame(
Date=sample(seq(as.Date('2018-10-25'), as.Date('2018-11-20'), by = "day"), 100,replace = T),
category1=sample(letters[1:6],100,replace = T),
count=sample(1:1000,100,replace = T)
)
answered Nov 20 '18 at 4:58
Jon SpringJon Spring
5,4131625
looks good and i have one doubt...we are comparing the 2 different date ranges but facet was used with another dates...can u please clarify how can we use dates in facet?
– sai saran
Nov 20 '18 at 5:14
2
Date is expressed here alternatively, as the number of whole weeks ago (weeks_ago), and the day of this week it would align with (adj_to_this_wk). You can facet toadj_to_this_wkbut then it would be formatted like "2018-11-14." To make it prettier, I made a formatted version callednice_dates, and made that a factor ordered by dates. Then it will show up as a string, but sorted chronologically instead of alphabetically.
– Jon Spring
Nov 20 '18 at 5:36
superb...thanks for the response and trying with real time usage data
– sai saran
Nov 20 '18 at 5:41
add a comment |
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1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
2
Here's an approach using facets, where I show each date of the last week as a facet, with the # of whole weeks prior on the x axis of each facet.
library(tidyverse)
df1 <- df %>%
mutate(days_old = (as.Date("2018-11-20") - Date) / lubridate::ddays(1),
weeks_ago = days_old %/% 7,
adj_to_this_week = as.Date("2018-11-20") - days_old %% 7) %>%
group_by(adj_to_this_week, weeks_ago, category1) %>%
summarise(Total=sum(count))
ggplot(df1 %>%
filter(weeks_ago <= 1) %>%
mutate(nice_dates = format(adj_to_this_week, "%b %d") %>%
fct_reorder(adj_to_this_wk)),
aes(-weeks_ago, Total,fill=category1)) +
geom_bar(stat = "identity",position = "stack",width = 0.8,alpha=0.8) +
scale_x_continuous(breaks = -1:0, labels = c("LW", "TW")) +
facet_wrap(~nice_dates, nrow = 1) +
labs(title = "Last week (LW) vs. This week (TW)", x ="") +
theme(panel.grid.major.x = element_blank(),
panel.grid.minor.x = element_blank())
Sample data:
set.seed(42)
df<-data.frame(
Date=sample(seq(as.Date('2018-10-25'), as.Date('2018-11-20'), by = "day"), 100,replace = T),
category1=sample(letters[1:6],100,replace = T),
count=sample(1:1000,100,replace = T)
)
answered Nov 20 '18 at 4:58
Jon SpringJon Spring
5,4131625
looks good and i have one doubt...we are comparing the 2 different date ranges but facet was used with another dates...can u please clarify how can we use dates in facet?
– sai saran
Nov 20 '18 at 5:14
2
Date is expressed here alternatively, as the number of whole weeks ago (weeks_ago), and the day of this week it would align with (adj_to_this_wk). You can facet toadj_to_this_wkbut then it would be formatted like "2018-11-14." To make it prettier, I made a formatted version callednice_dates, and made that a factor ordered by dates. Then it will show up as a string, but sorted chronologically instead of alphabetically.
– Jon Spring
Nov 20 '18 at 5:36
superb...thanks for the response and trying with real time usage data
– sai saran
Nov 20 '18 at 5:41
add a comment |
2
Here's an approach using facets, where I show each date of the last week as a facet, with the # of whole weeks prior on the x axis of each facet.
library(tidyverse)
df1 <- df %>%
mutate(days_old = (as.Date("2018-11-20") - Date) / lubridate::ddays(1),
weeks_ago = days_old %/% 7,
adj_to_this_week = as.Date("2018-11-20") - days_old %% 7) %>%
group_by(adj_to_this_week, weeks_ago, category1) %>%
summarise(Total=sum(count))
ggplot(df1 %>%
filter(weeks_ago <= 1) %>%
mutate(nice_dates = format(adj_to_this_week, "%b %d") %>%
fct_reorder(adj_to_this_wk)),
aes(-weeks_ago, Total,fill=category1)) +
geom_bar(stat = "identity",position = "stack",width = 0.8,alpha=0.8) +
scale_x_continuous(breaks = -1:0, labels = c("LW", "TW")) +
facet_wrap(~nice_dates, nrow = 1) +
labs(title = "Last week (LW) vs. This week (TW)", x ="") +
theme(panel.grid.major.x = element_blank(),
panel.grid.minor.x = element_blank())
Sample data:
set.seed(42)
df<-data.frame(
Date=sample(seq(as.Date('2018-10-25'), as.Date('2018-11-20'), by = "day"), 100,replace = T),
category1=sample(letters[1:6],100,replace = T),
count=sample(1:1000,100,replace = T)
)
answered Nov 20 '18 at 4:58
Jon SpringJon Spring
5,4131625
looks good and i have one doubt...we are comparing the 2 different date ranges but facet was used with another dates...can u please clarify how can we use dates in facet?
– sai saran
Nov 20 '18 at 5:14
2
Date is expressed here alternatively, as the number of whole weeks ago (weeks_ago), and the day of this week it would align with (adj_to_this_wk). You can facet toadj_to_this_wkbut then it would be formatted like "2018-11-14." To make it prettier, I made a formatted version callednice_dates, and made that a factor ordered by dates. Then it will show up as a string, but sorted chronologically instead of alphabetically.
– Jon Spring
Nov 20 '18 at 5:36
superb...thanks for the response and trying with real time usage data
– sai saran
Nov 20 '18 at 5:41
add a comment |
2
2
2
Here's an approach using facets, where I show each date of the last week as a facet, with the # of whole weeks prior on the x axis of each facet.
library(tidyverse)
df1 <- df %>%
mutate(days_old = (as.Date("2018-11-20") - Date) / lubridate::ddays(1),
weeks_ago = days_old %/% 7,
adj_to_this_week = as.Date("2018-11-20") - days_old %% 7) %>%
group_by(adj_to_this_week, weeks_ago, category1) %>%
summarise(Total=sum(count))
ggplot(df1 %>%
filter(weeks_ago <= 1) %>%
mutate(nice_dates = format(adj_to_this_week, "%b %d") %>%
fct_reorder(adj_to_this_wk)),
aes(-weeks_ago, Total,fill=category1)) +
geom_bar(stat = "identity",position = "stack",width = 0.8,alpha=0.8) +
scale_x_continuous(breaks = -1:0, labels = c("LW", "TW")) +
facet_wrap(~nice_dates, nrow = 1) +
labs(title = "Last week (LW) vs. This week (TW)", x ="") +
theme(panel.grid.major.x = element_blank(),
panel.grid.minor.x = element_blank())
Sample data:
set.seed(42)
df<-data.frame(
Date=sample(seq(as.Date('2018-10-25'), as.Date('2018-11-20'), by = "day"), 100,replace = T),
category1=sample(letters[1:6],100,replace = T),
count=sample(1:1000,100,replace = T)
)
answered Nov 20 '18 at 4:58
Jon SpringJon Spring
5,4131625
Here's an approach using facets, where I show each date of the last week as a facet, with the # of whole weeks prior on the x axis of each facet.
library(tidyverse)
df1 <- df %>%
mutate(days_old = (as.Date("2018-11-20") - Date) / lubridate::ddays(1),
weeks_ago = days_old %/% 7,
adj_to_this_week = as.Date("2018-11-20") - days_old %% 7) %>%
group_by(adj_to_this_week, weeks_ago, category1) %>%
summarise(Total=sum(count))
ggplot(df1 %>%
filter(weeks_ago <= 1) %>%
mutate(nice_dates = format(adj_to_this_week, "%b %d") %>%
fct_reorder(adj_to_this_wk)),
aes(-weeks_ago, Total,fill=category1)) +
geom_bar(stat = "identity",position = "stack",width = 0.8,alpha=0.8) +
scale_x_continuous(breaks = -1:0, labels = c("LW", "TW")) +
facet_wrap(~nice_dates, nrow = 1) +
labs(title = "Last week (LW) vs. This week (TW)", x ="") +
theme(panel.grid.major.x = element_blank(),
panel.grid.minor.x = element_blank())
Sample data:
set.seed(42)
df<-data.frame(
Date=sample(seq(as.Date('2018-10-25'), as.Date('2018-11-20'), by = "day"), 100,replace = T),
category1=sample(letters[1:6],100,replace = T),
count=sample(1:1000,100,replace = T)
)
answered Nov 20 '18 at 4:58
Jon SpringJon Spring
5,4131625
edited Nov 20 '18 at 5:34
answered Nov 20 '18 at 4:58
Jon SpringJon Spring
5,4131625
answered Nov 20 '18 at 4:58
Jon SpringJon Spring
5,4131625
answered Nov 20 '18 at 4:58
Jon SpringJon Spring
5,4131625
5,4131625
looks good and i have one doubt...we are comparing the 2 different date ranges but facet was used with another dates...can u please clarify how can we use dates in facet?
– sai saran
Nov 20 '18 at 5:14
2
Date is expressed here alternatively, as the number of whole weeks ago (weeks_ago), and the day of this week it would align with (adj_to_this_wk). You can facet toadj_to_this_wkbut then it would be formatted like "2018-11-14." To make it prettier, I made a formatted version callednice_dates, and made that a factor ordered by dates. Then it will show up as a string, but sorted chronologically instead of alphabetically.
– Jon Spring
Nov 20 '18 at 5:36
superb...thanks for the response and trying with real time usage data
– sai saran
Nov 20 '18 at 5:41
add a comment |
looks good and i have one doubt...we are comparing the 2 different date ranges but facet was used with another dates...can u please clarify how can we use dates in facet?
– sai saran
Nov 20 '18 at 5:14
2
Date is expressed here alternatively, as the number of whole weeks ago (weeks_ago), and the day of this week it would align with (adj_to_this_wk). You can facet toadj_to_this_wkbut then it would be formatted like "2018-11-14." To make it prettier, I made a formatted version callednice_dates, and made that a factor ordered by dates. Then it will show up as a string, but sorted chronologically instead of alphabetically.
– Jon Spring
Nov 20 '18 at 5:36
superb...thanks for the response and trying with real time usage data
– sai saran
Nov 20 '18 at 5:41
looks good and i have one doubt...we are comparing the 2 different date ranges but facet was used with another dates...can u please clarify how can we use dates in facet?
– sai saran
Nov 20 '18 at 5:14
looks good and i have one doubt...we are comparing the 2 different date ranges but facet was used with another dates...can u please clarify how can we use dates in facet?
– sai saran
Nov 20 '18 at 5:14
2
2
Date is expressed here alternatively, as the number of whole weeks ago (
weeks_ago), and the day of this week it would align with (adj_to_this_wk). You can facet to adj_to_this_wk but then it would be formatted like "2018-11-14." To make it prettier, I made a formatted version called nice_dates, and made that a factor ordered by dates. Then it will show up as a string, but sorted chronologically instead of alphabetically.– Jon Spring
Nov 20 '18 at 5:36
Date is expressed here alternatively, as the number of whole weeks ago (
weeks_ago), and the day of this week it would align with (adj_to_this_wk). You can facet to adj_to_this_wk but then it would be formatted like "2018-11-14." To make it prettier, I made a formatted version called nice_dates, and made that a factor ordered by dates. Then it will show up as a string, but sorted chronologically instead of alphabetically.– Jon Spring
Nov 20 '18 at 5:36
superb...thanks for the response and trying with real time usage data
– sai saran
Nov 20 '18 at 5:41
superb...thanks for the response and trying with real time usage data
– sai saran
Nov 20 '18 at 5:41
add a comment |
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i want to compare first data frame result with second data frame result like TOTAL count needs to be compare with one week to another week
– sai saran
Nov 20 '18 at 4:14
to know how the progress of total from one week to last week data
– sai saran
Nov 20 '18 at 4:14