How do I get a summary count of missing/NaN data by column in 'pandas'?

Question

In R I can quickly see a count of missing data using the summary command, but the equivalent pandas DataFrame method, describe

Answer 1

If you didn't care which columns had Nan's and you just wanted to check overall, just add a second .sum() to get a single value.

result = df.isnull().sum().sum()
result > 0

a Series would only need one .sum() and a Panel() would need three