Extract the values from the dataframes created in a loop for further analysis (I am not sure, how to sum up the question in one line) The Next CEO of Stack OverflowHow to make a great R reproducible exampleHow do I replace NA values with zeros in an R dataframe?Use a list of values to select rows from a pandas dataframeHow can I replace all the NaN values with Zero's in a column of a pandas dataframeHow to drop rows of Pandas DataFrame whose value in certain columns is NaNHow to get a value from a cell of a dataframe?Select rows from a DataFrame based on values in a column in pandasHow to count the NaN values in a column in pandas DataFrameHow to check if any value is NaN in a Pandas DataFrameTransforming panal dataForecast pop in the gapminder dataset and extract the predicted value in the same format as gapminder
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Extract the values from the dataframes created in a loop for further analysis (I am not sure, how to sum up the question in one line)
The Next CEO of Stack OverflowHow to make a great R reproducible exampleHow do I replace NA values with zeros in an R dataframe?Use a list of values to select rows from a pandas dataframeHow can I replace all the NaN values with Zero's in a column of a pandas dataframeHow to drop rows of Pandas DataFrame whose value in certain columns is NaNHow to get a value from a cell of a dataframe?Select rows from a DataFrame based on values in a column in pandasHow to count the NaN values in a column in pandas DataFrameHow to check if any value is NaN in a Pandas DataFrameTransforming panal dataForecast pop in the gapminder dataset and extract the predicted value in the same format as gapminder
My raw dataset has multiple product Id, monthly sales and corresponding date arranged in a matrix format. I wish to create individual dataframes for each product_id along with the sales value and dates. For this, I am using a for loop.
base is the base dataset.
x is the variable that contains the unique product_id and the corresponding no of observation points.
for(i in 1:nrow(x))
n <- paste("df", x$vars[i], sep = "")
assign(n, base[base[,1] == x$vars[i],])
print(n)
This is a part of the output:
[1] "df25"
[1] "df28"
[1] "df35"
[1] "df37"
[1] "df39"
So all the dataframe names are saved in n. This, I think is a string vector.
When I write df25 outside the loop, I get the dataframe I want:
> df25
# A tibble: 49 x 3
ID date Sales
<dbl> <date> <dbl>
1 25 2014-01-01 0
2 25 2014-02-01 0
3 25 2014-03-01 0
4 25 2014-04-01 0
5 25 2014-05-01 0
6 25 2014-06-01 0
7 25 2014-07-01 0
8 25 2014-08-01 0
9 25 2014-09-01 0
10 25 2014-10-01 0
# ... with 39 more rows
Now, I want to use each of these dataframes seperately to perform a forecast analysis. For doing this, I need to get to the values in individual dataframes. This is what I have tried for the same:
for(i in 1:4) print(paste0("df", x$vars[i]))
[1] "df2"
[1] "df3"
[1] "df5"
[1] "df14"
But I am unable to refer to individual dataframes.
I am looking for help on how can I get access to the dataframes with their values for further analysis? Since there are more than 200 products, I am looking for some function which deals with all the dataframes.
First, I wish to convert it to a TS, using year and month values from the date variable and then use ets or forecast, etc.
SAMPLE DATASET:
set.seed(354)
df <- data.frame(Product_Id = rep(1:10, each = 50),
Date = seq(from = as.Date("2014/1/1"), to = as.Date("2018/2/1") , by = "month"),
Sales = rnorm(100, mean = 50, sd= 20))
df <- df[-c(251:256, 301:312) ,]
As always, any suggestion would be highly appreciated.
r dataframe forecasting forecast
asked Mar 7 at 14:08
user10579790user10579790
819
add a comment |
My raw dataset has multiple product Id, monthly sales and corresponding date arranged in a matrix format. I wish to create individual dataframes for each product_id along with the sales value and dates. For this, I am using a for loop.
base is the base dataset.
x is the variable that contains the unique product_id and the corresponding no of observation points.
for(i in 1:nrow(x))
n <- paste("df", x$vars[i], sep = "")
assign(n, base[base[,1] == x$vars[i],])
print(n)
This is a part of the output:
[1] "df25"
[1] "df28"
[1] "df35"
[1] "df37"
[1] "df39"
So all the dataframe names are saved in n. This, I think is a string vector.
When I write df25 outside the loop, I get the dataframe I want:
> df25
# A tibble: 49 x 3
ID date Sales
<dbl> <date> <dbl>
1 25 2014-01-01 0
2 25 2014-02-01 0
3 25 2014-03-01 0
4 25 2014-04-01 0
5 25 2014-05-01 0
6 25 2014-06-01 0
7 25 2014-07-01 0
8 25 2014-08-01 0
9 25 2014-09-01 0
10 25 2014-10-01 0
# ... with 39 more rows
Now, I want to use each of these dataframes seperately to perform a forecast analysis. For doing this, I need to get to the values in individual dataframes. This is what I have tried for the same:
for(i in 1:4) print(paste0("df", x$vars[i]))
[1] "df2"
[1] "df3"
[1] "df5"
[1] "df14"
But I am unable to refer to individual dataframes.
I am looking for help on how can I get access to the dataframes with their values for further analysis? Since there are more than 200 products, I am looking for some function which deals with all the dataframes.
First, I wish to convert it to a TS, using year and month values from the date variable and then use ets or forecast, etc.
SAMPLE DATASET:
set.seed(354)
df <- data.frame(Product_Id = rep(1:10, each = 50),
Date = seq(from = as.Date("2014/1/1"), to = as.Date("2018/2/1") , by = "month"),
Sales = rnorm(100, mean = 50, sd= 20))
df <- df[-c(251:256, 301:312) ,]
As always, any suggestion would be highly appreciated.
r dataframe forecasting forecast
asked Mar 7 at 14:08
user10579790user10579790
819
1
side note: usually it is better practice not to assing new variables in a for loop, but use lists instead.
– Wimpel
Mar 7 at 14:10
I agree with @Wimpel. consider using lists and the purrr package. that should make this a lot easier from the start
– Bernd Konfuzius
Mar 7 at 14:31
Hey, can you please help me with some example? Are you suggesting to totally abandon for loop (I am quite new to R)?
– user10579790
Mar 7 at 14:38
@user10579790 please provide some sample-data, usingdput(). Further: read this: stackoverflow.com/questions/5963269/…
– Wimpel
Mar 7 at 15:00
Hey, I am adding a sample dataset as an edit to the question.
– user10579790
Mar 8 at 10:41
add a comment |
My raw dataset has multiple product Id, monthly sales and corresponding date arranged in a matrix format. I wish to create individual dataframes for each product_id along with the sales value and dates. For this, I am using a for loop.
base is the base dataset.
x is the variable that contains the unique product_id and the corresponding no of observation points.
for(i in 1:nrow(x))
n <- paste("df", x$vars[i], sep = "")
assign(n, base[base[,1] == x$vars[i],])
print(n)
This is a part of the output:
[1] "df25"
[1] "df28"
[1] "df35"
[1] "df37"
[1] "df39"
So all the dataframe names are saved in n. This, I think is a string vector.
When I write df25 outside the loop, I get the dataframe I want:
> df25
# A tibble: 49 x 3
ID date Sales
<dbl> <date> <dbl>
1 25 2014-01-01 0
2 25 2014-02-01 0
3 25 2014-03-01 0
4 25 2014-04-01 0
5 25 2014-05-01 0
6 25 2014-06-01 0
7 25 2014-07-01 0
8 25 2014-08-01 0
9 25 2014-09-01 0
10 25 2014-10-01 0
# ... with 39 more rows
Now, I want to use each of these dataframes seperately to perform a forecast analysis. For doing this, I need to get to the values in individual dataframes. This is what I have tried for the same:
for(i in 1:4) print(paste0("df", x$vars[i]))
[1] "df2"
[1] "df3"
[1] "df5"
[1] "df14"
But I am unable to refer to individual dataframes.
I am looking for help on how can I get access to the dataframes with their values for further analysis? Since there are more than 200 products, I am looking for some function which deals with all the dataframes.
First, I wish to convert it to a TS, using year and month values from the date variable and then use ets or forecast, etc.
SAMPLE DATASET:
set.seed(354)
df <- data.frame(Product_Id = rep(1:10, each = 50),
Date = seq(from = as.Date("2014/1/1"), to = as.Date("2018/2/1") , by = "month"),
Sales = rnorm(100, mean = 50, sd= 20))
df <- df[-c(251:256, 301:312) ,]
As always, any suggestion would be highly appreciated.
r dataframe forecasting forecast
asked Mar 7 at 14:08
user10579790user10579790
819
My raw dataset has multiple product Id, monthly sales and corresponding date arranged in a matrix format. I wish to create individual dataframes for each product_id along with the sales value and dates. For this, I am using a for loop.
base is the base dataset.
x is the variable that contains the unique product_id and the corresponding no of observation points.
for(i in 1:nrow(x))
n <- paste("df", x$vars[i], sep = "")
assign(n, base[base[,1] == x$vars[i],])
print(n)
This is a part of the output:
[1] "df25"
[1] "df28"
[1] "df35"
[1] "df37"
[1] "df39"
So all the dataframe names are saved in n. This, I think is a string vector.
When I write df25 outside the loop, I get the dataframe I want:
> df25
# A tibble: 49 x 3
ID date Sales
<dbl> <date> <dbl>
1 25 2014-01-01 0
2 25 2014-02-01 0
3 25 2014-03-01 0
4 25 2014-04-01 0
5 25 2014-05-01 0
6 25 2014-06-01 0
7 25 2014-07-01 0
8 25 2014-08-01 0
9 25 2014-09-01 0
10 25 2014-10-01 0
# ... with 39 more rows
Now, I want to use each of these dataframes seperately to perform a forecast analysis. For doing this, I need to get to the values in individual dataframes. This is what I have tried for the same:
for(i in 1:4) print(paste0("df", x$vars[i]))
[1] "df2"
[1] "df3"
[1] "df5"
[1] "df14"
But I am unable to refer to individual dataframes.
I am looking for help on how can I get access to the dataframes with their values for further analysis? Since there are more than 200 products, I am looking for some function which deals with all the dataframes.
First, I wish to convert it to a TS, using year and month values from the date variable and then use ets or forecast, etc.
SAMPLE DATASET:
set.seed(354)
df <- data.frame(Product_Id = rep(1:10, each = 50),
Date = seq(from = as.Date("2014/1/1"), to = as.Date("2018/2/1") , by = "month"),
Sales = rnorm(100, mean = 50, sd= 20))
df <- df[-c(251:256, 301:312) ,]
As always, any suggestion would be highly appreciated.
r dataframe forecasting forecast
r dataframe forecasting forecast
asked Mar 7 at 14:08
user10579790user10579790
819
asked Mar 7 at 14:08
user10579790user10579790
819
edited Mar 8 at 10:42
user10579790
asked Mar 7 at 14:08
user10579790user10579790
819
asked Mar 7 at 14:08
user10579790user10579790
819
asked Mar 7 at 14:08
user10579790user10579790
819
819
1
side note: usually it is better practice not to assing new variables in a for loop, but use lists instead.
– Wimpel
Mar 7 at 14:10
I agree with @Wimpel. consider using lists and the purrr package. that should make this a lot easier from the start
– Bernd Konfuzius
Mar 7 at 14:31
Hey, can you please help me with some example? Are you suggesting to totally abandon for loop (I am quite new to R)?
– user10579790
Mar 7 at 14:38
@user10579790 please provide some sample-data, usingdput(). Further: read this: stackoverflow.com/questions/5963269/…
– Wimpel
Mar 7 at 15:00
Hey, I am adding a sample dataset as an edit to the question.
– user10579790
Mar 8 at 10:41
add a comment |
1
side note: usually it is better practice not to assing new variables in a for loop, but use lists instead.
– Wimpel
Mar 7 at 14:10
I agree with @Wimpel. consider using lists and the purrr package. that should make this a lot easier from the start
– Bernd Konfuzius
Mar 7 at 14:31
Hey, can you please help me with some example? Are you suggesting to totally abandon for loop (I am quite new to R)?
– user10579790
Mar 7 at 14:38
@user10579790 please provide some sample-data, usingdput(). Further: read this: stackoverflow.com/questions/5963269/…
– Wimpel
Mar 7 at 15:00
Hey, I am adding a sample dataset as an edit to the question.
– user10579790
Mar 8 at 10:41
1
1
side note: usually it is better practice not to assing new variables in a for loop, but use lists instead.
– Wimpel
Mar 7 at 14:10
side note: usually it is better practice not to assing new variables in a for loop, but use lists instead.
– Wimpel
Mar 7 at 14:10
I agree with @Wimpel. consider using lists and the purrr package. that should make this a lot easier from the start
– Bernd Konfuzius
Mar 7 at 14:31
I agree with @Wimpel. consider using lists and the purrr package. that should make this a lot easier from the start
– Bernd Konfuzius
Mar 7 at 14:31
Hey, can you please help me with some example? Are you suggesting to totally abandon for loop (I am quite new to R)?
– user10579790
Mar 7 at 14:38
Hey, can you please help me with some example? Are you suggesting to totally abandon for loop (I am quite new to R)?
– user10579790
Mar 7 at 14:38
@user10579790 please provide some sample-data, using
dput(). Further: read this: stackoverflow.com/questions/5963269/…– Wimpel
Mar 7 at 15:00
@user10579790 please provide some sample-data, using
dput(). Further: read this: stackoverflow.com/questions/5963269/…– Wimpel
Mar 7 at 15:00
Hey, I am adding a sample dataset as an edit to the question.
– user10579790
Mar 8 at 10:41
Hey, I am adding a sample dataset as an edit to the question.
– user10579790
Mar 8 at 10:41
add a comment |
1 Answer
1
active
oldest
votes
I think this is one way to get an access to the individual dataframes. If there is a better method, please let me know:
(Var <- get(paste0("df",x$vars[i])))
answered Mar 8 at 13:46
user10579790user10579790
819
add a comment |
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I think this is one way to get an access to the individual dataframes. If there is a better method, please let me know:
(Var <- get(paste0("df",x$vars[i])))
answered Mar 8 at 13:46
user10579790user10579790
819
add a comment |
I think this is one way to get an access to the individual dataframes. If there is a better method, please let me know:
(Var <- get(paste0("df",x$vars[i])))
answered Mar 8 at 13:46
user10579790user10579790
819
add a comment |
I think this is one way to get an access to the individual dataframes. If there is a better method, please let me know:
(Var <- get(paste0("df",x$vars[i])))
answered Mar 8 at 13:46
user10579790user10579790
819
I think this is one way to get an access to the individual dataframes. If there is a better method, please let me know:
(Var <- get(paste0("df",x$vars[i])))
answered Mar 8 at 13:46
user10579790user10579790
819
answered Mar 8 at 13:46
user10579790user10579790
819
answered Mar 8 at 13:46
user10579790user10579790
819
answered Mar 8 at 13:46
user10579790user10579790
819
819
add a comment |
add a comment |
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1
side note: usually it is better practice not to assing new variables in a for loop, but use lists instead.
– Wimpel
Mar 7 at 14:10
I agree with @Wimpel. consider using lists and the purrr package. that should make this a lot easier from the start
– Bernd Konfuzius
Mar 7 at 14:31
Hey, can you please help me with some example? Are you suggesting to totally abandon for loop (I am quite new to R)?
– user10579790
Mar 7 at 14:38
@user10579790 please provide some sample-data, using
dput(). Further: read this: stackoverflow.com/questions/5963269/…– Wimpel
Mar 7 at 15:00
Hey, I am adding a sample dataset as an edit to the question.
– user10579790
Mar 8 at 10:41