How it works...
The first step replicates work from the previous recipe by converting two columns to numeric and eliminating the binary columns. We find the maximum value of each column in step 2. Care needs to be taken here as pandas silently drops columns that it cannot produce a maximum. If this happens, then step 3 will still complete but produce all False values for each column without an available maximum.
Step 4 uses the any method to scan across each row in search of at least one True value. Any row with at least one True value contains a maximum value for a column. We sum up the resulting boolean Series in step 5 to determine how many rows contain a maximum. Somewhat unexpectedly, there are far more rows than columns. Step 6 gives ...
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