I'm currently trying to find a pythonic way to "translate" the below R code which takes in a dataframe with three columns titled "strikeDeg", "dipDeg" and "rakeDeg" and appends it with three columns:
This is part of a larger if-loop to parse the original dataframe depending on what columns are not NULL.
geoPoleDirectionRotationFromData <- function(dataFrame) {
newFrame <- emptyDataFrame(nrow(dataFrame))
# Make rotation, pole, direction from strike, dip, rake.
newFrame$rotation <- lapply(1:nrow(dataFrame),
function(i) geoRotationFromStrikeDipRakeDeg(
c(dataFrame[i,]$strikeDeg, dataFrame[i,]$dipDeg, dataFrame[i,]$rakeDeg)))
newFrame$pole <- lapply(1:nrow(newFrame), function(i) newFrame$rotation[[i]][1,])
newFrame$direction <- lapply(1:nrow(newFrame), function(i) newFrame$rotation[[i]][2,])
newFrame
The part of the code in question is how can I perform lapply() functions in each of the 3 new columns on the 3 existing columns of the input dataFrame in python? Would I have to create a vector from the existing columns of the dataFrame and apply a map() function?
you can just use the apply function, and specify axis to match the dimension you want to apply it.
you can see an example in the following link
simple example for applying function on column:
import pandas as pd
matrix = [(222, 34, 23),
(333, 31, 11),
(444, 16, 21),
(555, 32, 22),
(666, 33, 27),
(777, 35, 11)
]
# Create a DataFrame object
dfObj = pd.DataFrame(matrix, columns=list('abc'))
print(dfObj)
modDfObj = dfObj.apply(lambda x : x + 10)
print(modDfObj)
I get the following output:
a b c
0 222 34 23
1 333 31 11
2 444 16 21
3 555 32 22
4 666 33 27
5 777 35 11
a b c
0 232 44 33
1 343 41 21
2 454 26 31
3 565 42 32
4 676 43 37
5 787 45 21
You can see that the only change was in the all the columns and you can easily generalize it to your desire. (for instance) for applying to a specific column or columns you can change the apply line to either options:
modDfObj = dfObj.apply(lambda x: x + 10 if x.name == 'b' else x)
modDfObj = dfObj.apply(lambda x: x + 10 if (x.name == 'b' or x.name == 'c') else x)
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