Pandas efficiently add new column true/false if between two other columns

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Using Pandas, how can I efficiently add a new column that is true/false if the value in one column (x) is between the values in two other columns (low and high)?

The np.select approach from here works perfectly, but I "feel" like there should be a one-liner way to do this.

Using Python 3.7

fid = [0, 1, 2, 3, 4]
x = [0.18, 0.07, 0.11, 0.3, 0.33]
low = [0.1, 0.1, 0.1, 0.1, 0.1]
high = [0.2, 0.2, 0.2, 0.2, 0.2]
test = pd.DataFrame(data=zip(fid, x, low, high), columns=["fid", "x", "low", "high"])

conditions = [(test["x"] >= test["low"]) & (test["x"] <= test["high"])]
labels = ["True"]
test["between"] = np.select(conditions, labels, default="False")

display(test)

enter image description here

pandas numpy python
1 Answers

Like mentioned by @Brebdan, you can use this builtin:

test["between"] = test["x"].between(test["low"], test["high"])

output:

    fid x   low high    between
0   0   0.18    0.1 0.2 True
1   1   0.07    0.1 0.2 False
2   2   0.11    0.1 0.2 True
3   3   0.30    0.1 0.2 False
4   4   0.33    0.1 0.2 False
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