Pandas DataFrame值循环转换报错求助：将n/y/?转为0/1/0

Got it, let's fix this issue step by step. First, the error you're seeing happens because when you use df.names in your loop, Python is trying to access an attribute named names on the DataFrame (which doesn't exist) instead of the column whose name is stored in your names variable. You need to use bracket notation df[names] to dynamically access columns by their name.

Fixed Loop Approach #

Here's your original code adjusted to work correctly:

for col_name in df.columns.values:
    # Replace 'n'→0 and 'y'→1 first
    df[col_name].replace(('n', 'y'), (0, 1), inplace=True)
    # Replace '?'→0 next
    df[col_name].replace('?', 0, inplace=True)
    # Convert the column to integer type explicitly
    df[col_name] = df[col_name].astype(int)

More Efficient One-Liner Approach #

Instead of looping through each column manually, you can handle all columns in one go with a single replace call—this is cleaner and faster for large DataFrames:

# Define a mapping dictionary for all values
value_mapping = {'n': 0, 'y': 1, '?': 0}
# Apply the mapping to the entire DataFrame and convert to integers
df = df.replace(value_mapping).astype(int)

Alternative: Using applymap #

If you prefer a functional approach, applymap lets you apply a custom function to every element in the DataFrame:

def convert_to_numeric(val):
    return 1 if val == 'y' else 0
    # This handles both 'n' and '?' cases by returning 0

df = df.applymap(convert_to_numeric).astype(int)

Verify the Result #

After running any of these methods, you can check the output with df.head() to confirm all values are now integers:

party infants water budget physician salvador religious satellite aid missile immigration synfuels education superfund crime duty_free_exports eaa_rsa
0       0       1     0       1         1        1          0         0   0       0            1         0         1         1     1                  0       1
1       0       1     0       1         1        1          0         0   0       0            0         0         1         1     1                  0       0
2       0       1     1       0         1        1          0         0   0       0            0         1         0         1     1                  0       0
3       0       1     1       0         0        1          0         0   0       0            0         1         0         1     0                  0       1
4       1       1     1       0         1        1          0         0   0       0            0         1         0         1     1                  1       1

内容的提问来源于stack exchange，提问作者JL1829