Replacing NaN with Mean of Values

delta.py

df['ENTRY_DELTA'][df['ENTRY_DELTA']>10000]=np.nan
df['ENTRY_DELTA'][df['ENTRY_DELTA']<0]=np.nan
# Setting the anomaly values due to reset of counters to the uniform NaN values

delta_list = list(df['ENTRY_DELTA'])
ind = 0
for i in delta_list:
    if np.isnan(i) == 1:
        delta_list[ind] = np.nanmean([delta_list[ind-1],delta_list[ind+1]])
    ind += 1
    
df['ENTRY_DELTA_1'] = delta_list 
# for each NaN values, replace it with the mean of values before and after the NaN value