Can Pandas perform row-wise min() and max() functions?

Question

In my DataFrame I wish to clip the value of a particular column between 0 and 100. For instance, given the following:

  a  b
0 10 90
1 20 150
2 30 -30

I want to get:

  a  b   c
0 10 90  90
1 20 150 100
2 30 -30 0

I know that in Pandas certain arithmetic operations work across columns. For instance, I could double every number in column b like so:

>>>df["c"] = df["b"] * 2
>>>df
  a  b   c
0 10 90  180
1 20 150 300
2 30 -30 -60

However this doesn't work for built-in functions like min and max:

>>>df["c"] = min(100, max(0, df["b"]))
ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().

Is there some way to accomplish what I want efficiently?

Answer 1

You can use the Pandas min function across an axis. Then combine it with min/max

https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.min.html

For example

df.max(axis=1)

But it looks like you want to clip the values instead of min/max.