Using Apply in Pandas Lambda functions with multiple if statements

Question

I\'m trying to infer a classification according to the size of a person in a dataframe like this one:

      Size
1     80000
2     8000000
3     8000000000
...
<         


        

Answer 1

Using Numpy's searchsorted

labels = np.array(['<1m', '1-10m', '10-50m', '>50m'])
bins = np.array([1E6, 1E7, 5E7])

# Using assign is my preference as it produces a copy of df with new column
df.assign(Classification=labels[bins.searchsorted(df['Size'].values)])

If you wanted to produce new column in existing dataframe

df['Classification'] = labels[bins.searchsorted(df['Size'].values)]

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Some Explanation

From Docs:np.searchsorted

Find indices where elements should be inserted to maintain order.

Find the indices into a sorted array a such that, if the corresponding elements in v were inserted before the indices, the order of a would be preserved.

The labels array has a length greater than that of bins by one. Because when something is greater than the maximum value in bins, searchsorted returns a -1. When we slice labels this grabs the last label.