如何仅在满足第一个条件时才评估第二个条件？

Question

I made a DataFrame in Pandas and made a DataFrame like below.

if (a['conversion'] == line.strip().any() \
    or (a['x'] == line.strip().any() \
    or (a['y'] == line.strip().any() \
    or (a['z'] == line.strip().any():
    generate(line)
    

so basically, I would like to check both keys x, y and z but some types does not have key 'y' or 'z'. So KeyError: 'y' was raised.

How can I only approach existing keys? or do I have to use try/except? or if I have to use.get(['y]) function, how can I implement it? (it did not really work)

Answer 1

You have two approaches:

1. Check if a column exists (Look Before You Leap):

    if df['conversion'] == line.strip().any() \ or df['x'] == line.strip().any() \ # Checking if the columns are part of the dataframe or ('y' in df.columns and df['y'] == line.strip().any()) \ or ('z' in df.columns and df['z'] == line.strip().any()): generate(line)

   or

   columns = ('conversion', 'x', 'y', 'z') for column in columns: # If this column is not present, just keep looking if column not in df: continue if df[column] == line.strip().any(): generate(line) break

2. Try to access the damn column anyway (Easier to Ask for Forgiveness than Permission):

    condition = False columns = ('conversion', 'x', 'y', 'z') for column in columns: try: # Update the condition using the or clause condition = df[column] == line.strip().any() except KeyError: # If the key is not present, just keep looking continue else: # Use short-circuiting if condition: generate(line) break