Pandas Dataframe 替换异常值

Question

Thank you in advance for your help! (Code Provided Below) (Data Here )

I would like to remove the outliers outside of 5/6th standard deviation for columns 5 cm through 225 cm and replace them with the average value for that date (Month/Day) and depth. What is the best way to do that?

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import warnings
warnings.filterwarnings('ignore')
raw_data = pd.read_csv('all-deep-soil-temperatures.csv', index_col=1, parse_dates=True)
df_all_stations = raw_data.copy()
df_selected_station.fillna(method = 'ffill', inplace=True);
df_selected_station_D=df_selected_station.resample(rule='D').mean()
df_selected_station_D['Day'] = df_selected_station_D.index.dayofyear
mean=df_selected_station_D.groupby(by='Day').mean()
mean['Day']=mean.index
mean.head()

Answer 1

For a more general solution, assuming that you are given a dataframe df with some column a .

from scipy import stats.
df[np.abs(stats.zscore(df['a'])) > 5]['a'] = df['a'].mean()