Coming from R
to Python
and I can't seem to figure out a simple case of creating a new column, based on conditionally checking other columns.
# In R, create a 'z' column based on values in x and y columns
df <- data.frame(x=rnorm(100),y=rnorm(100))
df$z <- ifelse(df$x > 1.0 | df$y < -1.0, 'outlier', 'normal')
table(df$z)
# output below
normal outlier
66 34
Attempt at the equivalent statement in Python:
import numpy as np
import pandas as pd
df = pd.DataFrame({'x': np.random.standard_normal(100), 'y': np.random.standard_normal(100)})
df['z'] = 'outlier' if df.x > 1.0 or df.y < -1.0 else 'normal'
However, the following exception is thrown:
ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().
What is the pythonic way of achieving this? Many thanks :)