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How to add a new column in data frame by dividing values in an existing column, specifically, in the same...
I want to use the mutate function to create a new column.
I can't figure out how to do it because the values in the new column are to be quotients of values from another column in my data frame.
Usually when I've used mutate before the values were in different columns like mutate(newcolumn = colX_values / colY_values) but this time, both parts of the equation are in the same column. The main difference is that I want the female values to be divided by the male values.
```{r}
library(tidyverse)
library(ggplot2)
library(readxl)
```
```{r}
race = c("all", "all", "black", "black")
earnings = c(74467, 57202, 44725, 40974)
gender = c("male", "female", "male", "female")
work_status = c("FT", "FT", "FT", "FT")
data.frame(race, earnings, gender, work_status)
```
```{r}
earnings %>%
filter(work_status == "FT")
```
I eventually want a 5th column that consists of the the female earnings / male earnings per each race. so for all the male rows there should be the number 1 in the new column and in all the female rows it should be the result of 57202/74467.
I am just not sure how to get that result.
r tidyverse mutate
edited Jan 2 at 8:14
NelsonGon
3,2803832
asked Dec 31 '18 at 21:41
Josephine AnkrahJosephine Ankrah
103
add a comment |
I want to use the mutate function to create a new column.
I can't figure out how to do it because the values in the new column are to be quotients of values from another column in my data frame.
Usually when I've used mutate before the values were in different columns like mutate(newcolumn = colX_values / colY_values) but this time, both parts of the equation are in the same column. The main difference is that I want the female values to be divided by the male values.
```{r}
library(tidyverse)
library(ggplot2)
library(readxl)
```
```{r}
race = c("all", "all", "black", "black")
earnings = c(74467, 57202, 44725, 40974)
gender = c("male", "female", "male", "female")
work_status = c("FT", "FT", "FT", "FT")
data.frame(race, earnings, gender, work_status)
```
```{r}
earnings %>%
filter(work_status == "FT")
```
I eventually want a 5th column that consists of the the female earnings / male earnings per each race. so for all the male rows there should be the number 1 in the new column and in all the female rows it should be the result of 57202/74467.
I am just not sure how to get that result.
r tidyverse mutate
edited Jan 2 at 8:14
NelsonGon
3,2803832
asked Dec 31 '18 at 21:41
Josephine AnkrahJosephine Ankrah
103
Sorry please disregard the filtering.
– Josephine Ankrah
Dec 31 '18 at 21:43
1
hmmm, so I created a new column using `mutate(new_earnings = c("74467", "74467", "44725", "44725")). and now I plan to just divide that way. I am still curious if there is a more direct way to go about solving this.
– Josephine Ankrah
Dec 31 '18 at 21:50
add a comment |
I want to use the mutate function to create a new column.
I can't figure out how to do it because the values in the new column are to be quotients of values from another column in my data frame.
Usually when I've used mutate before the values were in different columns like mutate(newcolumn = colX_values / colY_values) but this time, both parts of the equation are in the same column. The main difference is that I want the female values to be divided by the male values.
```{r}
library(tidyverse)
library(ggplot2)
library(readxl)
```
```{r}
race = c("all", "all", "black", "black")
earnings = c(74467, 57202, 44725, 40974)
gender = c("male", "female", "male", "female")
work_status = c("FT", "FT", "FT", "FT")
data.frame(race, earnings, gender, work_status)
```
```{r}
earnings %>%
filter(work_status == "FT")
```
I eventually want a 5th column that consists of the the female earnings / male earnings per each race. so for all the male rows there should be the number 1 in the new column and in all the female rows it should be the result of 57202/74467.
I am just not sure how to get that result.
r tidyverse mutate
edited Jan 2 at 8:14
NelsonGon
3,2803832
asked Dec 31 '18 at 21:41
Josephine AnkrahJosephine Ankrah
103
I want to use the mutate function to create a new column.
I can't figure out how to do it because the values in the new column are to be quotients of values from another column in my data frame.
Usually when I've used mutate before the values were in different columns like mutate(newcolumn = colX_values / colY_values) but this time, both parts of the equation are in the same column. The main difference is that I want the female values to be divided by the male values.
```{r}
library(tidyverse)
library(ggplot2)
library(readxl)
```
```{r}
race = c("all", "all", "black", "black")
earnings = c(74467, 57202, 44725, 40974)
gender = c("male", "female", "male", "female")
work_status = c("FT", "FT", "FT", "FT")
data.frame(race, earnings, gender, work_status)
```
```{r}
earnings %>%
filter(work_status == "FT")
```
I eventually want a 5th column that consists of the the female earnings / male earnings per each race. so for all the male rows there should be the number 1 in the new column and in all the female rows it should be the result of 57202/74467.
I am just not sure how to get that result.
r tidyverse mutate
r tidyverse mutate
edited Jan 2 at 8:14
NelsonGon
3,2803832
asked Dec 31 '18 at 21:41
Josephine AnkrahJosephine Ankrah
103
edited Jan 2 at 8:14
NelsonGon
3,2803832
asked Dec 31 '18 at 21:41
Josephine AnkrahJosephine Ankrah
103
edited Jan 2 at 8:14
NelsonGon
3,2803832
edited Jan 2 at 8:14
NelsonGon
3,2803832
edited Jan 2 at 8:14
NelsonGon
3,2803832
3,2803832
asked Dec 31 '18 at 21:41
Josephine AnkrahJosephine Ankrah
103
asked Dec 31 '18 at 21:41
Josephine AnkrahJosephine Ankrah
103
asked Dec 31 '18 at 21:41
Josephine AnkrahJosephine Ankrah
103
103
Sorry please disregard the filtering.
– Josephine Ankrah
Dec 31 '18 at 21:43
1
hmmm, so I created a new column using `mutate(new_earnings = c("74467", "74467", "44725", "44725")). and now I plan to just divide that way. I am still curious if there is a more direct way to go about solving this.
– Josephine Ankrah
Dec 31 '18 at 21:50
add a comment |
Sorry please disregard the filtering.
– Josephine Ankrah
Dec 31 '18 at 21:43
1
hmmm, so I created a new column using `mutate(new_earnings = c("74467", "74467", "44725", "44725")). and now I plan to just divide that way. I am still curious if there is a more direct way to go about solving this.
– Josephine Ankrah
Dec 31 '18 at 21:50
Sorry please disregard the filtering.
– Josephine Ankrah
Dec 31 '18 at 21:43
Sorry please disregard the filtering.
– Josephine Ankrah
Dec 31 '18 at 21:43
1
1
hmmm, so I created a new column using `mutate(new_earnings = c("74467", "74467", "44725", "44725")). and now I plan to just divide that way. I am still curious if there is a more direct way to go about solving this.
– Josephine Ankrah
Dec 31 '18 at 21:50
hmmm, so I created a new column using `mutate(new_earnings = c("74467", "74467", "44725", "44725")). and now I plan to just divide that way. I am still curious if there is a more direct way to go about solving this.
– Josephine Ankrah
Dec 31 '18 at 21:50
add a comment |
1 Answer
1
active
oldest
votes
Is this what you're looking for?
df %>%
spread(gender,earnings) %>%
mutate(Ratio=female/male)
Output:
race work_status female male Ratio
1 all FT 57202 74467 0.7681523
2 black FT 40974 44725 0.9161319
answered Jan 1 at 23:54
NelsonGonNelsonGon
3,2803832
1
yes! exactly. thank you very much.
– Josephine Ankrah
Jan 2 at 15:38
Glad it helped. Cheers!
– NelsonGon
Jan 2 at 15:43
add a comment |
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1 Answer
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active
oldest
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1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
Is this what you're looking for?
df %>%
spread(gender,earnings) %>%
mutate(Ratio=female/male)
Output:
race work_status female male Ratio
1 all FT 57202 74467 0.7681523
2 black FT 40974 44725 0.9161319
answered Jan 1 at 23:54
NelsonGonNelsonGon
3,2803832
1
yes! exactly. thank you very much.
– Josephine Ankrah
Jan 2 at 15:38
Glad it helped. Cheers!
– NelsonGon
Jan 2 at 15:43
add a comment |
Is this what you're looking for?
df %>%
spread(gender,earnings) %>%
mutate(Ratio=female/male)
Output:
race work_status female male Ratio
1 all FT 57202 74467 0.7681523
2 black FT 40974 44725 0.9161319
answered Jan 1 at 23:54
NelsonGonNelsonGon
3,2803832
1
yes! exactly. thank you very much.
– Josephine Ankrah
Jan 2 at 15:38
Glad it helped. Cheers!
– NelsonGon
Jan 2 at 15:43
add a comment |
Is this what you're looking for?
df %>%
spread(gender,earnings) %>%
mutate(Ratio=female/male)
Output:
race work_status female male Ratio
1 all FT 57202 74467 0.7681523
2 black FT 40974 44725 0.9161319
answered Jan 1 at 23:54
NelsonGonNelsonGon
3,2803832
Is this what you're looking for?
df %>%
spread(gender,earnings) %>%
mutate(Ratio=female/male)
Output:
race work_status female male Ratio
1 all FT 57202 74467 0.7681523
2 black FT 40974 44725 0.9161319
answered Jan 1 at 23:54
NelsonGonNelsonGon
3,2803832
answered Jan 1 at 23:54
NelsonGonNelsonGon
3,2803832
answered Jan 1 at 23:54
NelsonGonNelsonGon
3,2803832
answered Jan 1 at 23:54
NelsonGonNelsonGon
3,2803832
3,2803832
1
yes! exactly. thank you very much.
– Josephine Ankrah
Jan 2 at 15:38
Glad it helped. Cheers!
– NelsonGon
Jan 2 at 15:43
add a comment |
1
yes! exactly. thank you very much.
– Josephine Ankrah
Jan 2 at 15:38
Glad it helped. Cheers!
– NelsonGon
Jan 2 at 15:43
1
1
yes! exactly. thank you very much.
– Josephine Ankrah
Jan 2 at 15:38
yes! exactly. thank you very much.
– Josephine Ankrah
Jan 2 at 15:38
Glad it helped. Cheers!
– NelsonGon
Jan 2 at 15:43
Glad it helped. Cheers!
– NelsonGon
Jan 2 at 15:43
add a comment |
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Sorry please disregard the filtering.
– Josephine Ankrah
Dec 31 '18 at 21:43
1
hmmm, so I created a new column using `mutate(new_earnings = c("74467", "74467", "44725", "44725")). and now I plan to just divide that way. I am still curious if there is a more direct way to go about solving this.
– Josephine Ankrah
Dec 31 '18 at 21:50