The background is, I have a table of z-score values that I would like to convert to CDF values of the norm distribution. I'm currently using
scipy for this.
I'm currently manipulating a dataframe that has non-numeric values.
Name Val1 Val2 Val3 Val4 0 A -1.540369 -0.077779 0.979606 -0.667112 1 B -0.787154 0.048412 0.775444 -0.510904 2 C -0.477234 0.414388 1.250544 -0.411658 3 D -1.430851 0.258759 1.247752 -0.883293 4 E -0.360181 0.485465 1.123589 -0.379157
Name variable an index is a solution, but in my actual dataset, the names are not alphabetical characters.)
To modify only the numeric data, I'm using
df._get_numeric_data() a private function that returns a dataframe containing a dataframe's numeric data. However, there is no
set function. Hence, if I call
this won't change
df's original data.
I'm trying to circumvent this by applying
norm.cdf to the numeric dataframe inplace, so this changes my original dataset.