How to iterate through pandas columns?-CodePudding

I have a df that looks like this:

measurement_3      329
measurement_4      409
measurement_5      508
measurement_6      624
measurement_7      720
measurement_8      846
measurement_9      904
measurement_10    1067
measurement_11    1136
measurement_12    1240
measurement_13    1303
measurement_14    1440
measurement_15    1542
measurement_16    1678
measurement_17    1740

How do I iterate through the column names so that I can get the mean of each column without manually doing it?

I have done the following, but would like a more optimised solution using a for loop:

# Mean
dataset['loading'].fillna(dataset['loading'].mean(), inplace=True)

# Mean   std

dataset['measurement_3'].fillna(dataset['measurement_3'].mean()   dataset['measurement_3'].std(), inplace=True)
dataset['measurement_4'].fillna(dataset['measurement_4'].mean()   dataset['measurement_4'].std(), inplace=True)
dataset['measurement_5'].fillna(dataset['measurement_5'].mean()   dataset['measurement_5'].std(), inplace=True)
# continues to measurement_17

CodePudding user response：

Please say no to looping...

measures = df.filter(like='measurement')
df[measures.columns] = measures.fillna(measures.mean()   measures.std())

CodePudding user response：

for i in range(3,18):
    dataset[f'measurement_{i}'].fillna(dataset[f'measurement_{i}'].mean()   dataset[f'measurement_{i}'].std(), inplace=True)

use for loop with f-string format to access data frame column using name