Parsing a JSON string which was loaded from a CSV using Pandas

Question

I am working with CSV files where several of the columns have a simple json object (several key value pairs) while other columns are normal. Here is an example:

Answer 1

Paul's original answer was very nice but not correct in general, because there is no assurance that the ordering of columns is the same on the left-hand side and the right-hand side of the last line. (In fact, it does not seem to work on the test data in the question, instead erroneously switching the height and weight columns.)

We can fix this by ensuring that the list of dict keys on the LHS is sorted. This works because the apply on the RHS automatically sorts by the index, which in this case is the list of column names.

def CustomParser(data):
  import json
  j1 = json.loads(data)
  return j1

df = pandas.read_csv(f1, converters={'stats':CustomParser},header=0)
df[sorted(df['stats'][0].keys())] = df['stats'].apply(pandas.Series)