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This is the following R code.
mutate(Loan_Status_delinquency = ifelse(EOM_Delinq_Bucket %in% c(1, 2, 3, 4), "Yes", "No"))
I want this to be convert into Python
Thanks in advance.
You can try
df['result'] = df.Loan_Status_delinquency.isin([1,2,3,4]).replace({ True : 'Yes', False : 'No'})
df[['new_columm']] = df.Loan_Status_delinquency.apply(lambda x: "Yes" if x in [1,2,3,4] else "No")
Will add a column new_column onto your pandas dataframe df. In the future please have a go and we can look at your attempt - it'll mean you have to come here less often!
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I have a dataset with time, where the time intervals are 6 hours apart and I have a column of heaterstatus.
The dataset :
I would like to know the percentage of zero occurred in each day for heaterstatus. New to R, any suggestion will be helpful.
Not tested since you only provided data as an image, but this should do what you want:
library(dplyr)
dat %>%
group_by(day = as.Date(Time)) %>%
summarize(pct_0 = mean(HeaterStatus == 0))
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I have 16 variables that are numeric, and I need to create an extra column that is YES (otherwise NO) when 3 or more variables out of those 16 have a value above 1015.
How could I do that?
Thanks
You can try with rowSums :
cols <- 1:16
df$res <- ifelse(rowSums(df[cols] > 1015, na.rm = TRUE) >= 3, 'Yes', 'No')
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How can I make the following changes for multiple or all variables?
change "yes" to 1
change "no" to 0
keep NAs
I tried recode but it seems not to be appliable to dataframes.
x <- data.frame(y=sample(c("yes", "no", "NA"), 10, replace = TRUE))
library(tidyr)
x$y2<- recode_factor(x$y, yes=1, no=0)
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dat = runif(10,1,10)
dat2 = runif(10,1,10)
dat3 = runif(10,1,10)
data = rbind(dat,dat2,dat3)
In the case of above data, I am wondering how I can filter out rows as long as there is one element in that row exceeding 5.
I know that I can use loop to achieve this, but I am wondering if there is more succinct way to do this.
try this:
data[apply(data>5, 1, sum)>0,]
This says "for condition having more than zero number exceeding 5 in each row, filter data".
data[do.call(pmax,data.frame(data))<=5,]
Cheers,
Bert
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Lets say I have a vector c(1,2,3,4,5,6,7,8,9) how can I get a print of just 1,3,and 5 ?
For a sample of n random elements from vector X you can use sample(x = X, size = 3, replace = FALSE). To get the ith element of X you simply use X[i].