Replace Logical Values (True/False) with Numeric (1/0)

Replace logical values (TRUE / FALSE) with numeric (1 / 0)

For a data.frame, you could convert all logical columns to numeric with:

# The data
set.seed(144)
dat <- data.frame(V1=1:100,V2=rnorm(100)>0)
dat$V3 <- dat$V2 == 1
head(dat)
#   V1    V2    V3
# 1  1 FALSE FALSE
# 2  2  TRUE  TRUE
# 3  3 FALSE FALSE
# 4  4 FALSE FALSE
# 5  5 FALSE FALSE
# 6  6  TRUE  TRUE

# Convert all to numeric
cols <- sapply(dat, is.logical)
dat[,cols] <- lapply(dat[,cols], as.numeric)
head(dat)
#   V1 V2 V3
# 1  1  0  0
# 2  2  1  1
# 3  3  0  0
# 4  4  0  0
# 5  5  0  0
# 6  6  1  1

In data.table syntax:

# Data
set.seed(144)
DT = data.table(cbind(1:100,rnorm(100)>0))
DT[,V3 := V2 == 1]
DT[,V4 := FALSE]
head(DT)
#    V1 V2    V3    V4
# 1:  1  0 FALSE FALSE
# 2:  2  1  TRUE FALSE
# 3:  3  0 FALSE FALSE
# 4:  4  0 FALSE FALSE
# 5:  5  0 FALSE FALSE
# 6:  6  1  TRUE FALSE

# Converting
(to.replace <- names(which(sapply(DT, is.logical))))
# [1] "V3" "V4"
for (var in to.replace) DT[, (var):= as.numeric(get(var))]
head(DT)
#    V1 V2 V3 V4
# 1:  1  0  0  0
# 2:  2  1  1  0
# 3:  3  0  0  0
# 4:  4  0  0  0
# 5:  5  0  0  0
# 6:  6  1  1  0

converting logical true/false to numeric 1/0?

You can write (if x > param then 1 else 0)*f(x) for example.

You can also write charfun(x > param)*f(x). See ? charfun.

Convert dataframe column to 1 or 0 for true/false values and assign to dataframe

@chappers solution (in the comments) works as.integer(as.logical(data.frame$column.name))

How can I map True/False to 1/0 in a Pandas DataFrame?

A succinct way to convert a single column of boolean values to a column of integers 1 or 0:

df["somecolumn"] = df["somecolumn"].astype(int)

Converting all occurrence of True/False to 1/0 in a dataframe with mixed datatype

applymap is not in-place by default, it will return a new dataframe.

The correct way:

test = test.applymap(lambda x: 1 if x == True else x)
test = test.applymap(lambda x: 0 if x == False else x)

or

test = test.applymap(lambda x: 1 if x == True else x).test.applymap(lambda x: 0 if x=='False' else x)

or simply

test.applymap(lambda x: 1 if x == True else x, inplace=True)
test.applymap(lambda x: 0 if x == False else x, inplace=True)

Although replace seems the best way of achieving this:

test.replace(False, 0, inplace=True)

Change 0/1 values to TRUE/FALSE in R

Use x1 == 1:

> x1 == 1
      [,1] [,2]
[1,]  TRUE TRUE
[2,] FALSE TRUE
> 

Or use x1 == TRUE:

> x1 == TRUE
      [,1] [,2]
[1,]  TRUE TRUE
[2,] FALSE TRUE
> 

Or with apply and as.logical:

> apply(x1, 2, as.logical)
     [,1]  [,2]
[1,] TRUE FALSE
[2,] TRUE  TRUE
> 

Change values in df to 0 = FALSE, 1 = TRUE, 2 = TRUE

You can use mutate_if to change numeric columns to their logical equivalents:

test %>% mutate_if(is.numeric,as.logical)
  ID Primary Secondary Tertiary
1  A   FALSE      TRUE     TRUE
2  B   FALSE     FALSE     TRUE
3  C    TRUE      TRUE    FALSE
4  D    TRUE      TRUE    FALSE

How to convert 'false' to 0 and 'true' to 1?

Use int() on a boolean test:

x = int(x == 'true')

int() turns the boolean into 1 or 0. Note that any value not equal to 'true' will result in 0 being returned.

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