pandas df after fillna() is still NaN - pandas

Question

A 40000 rows 1 column data saved as excel. There are hundred null values in it. Such as row 361...
When I carried out df.fillna(method='bfill'), the NaN values is still NaN.
If sliced a df fragment contained Null values, it processed expectently.
I tried but still could not fill NaN cells.
So what's wrong with it?
The df file is here:
excel file click here
df=pd.read_execel('npp.xlsx')
df.fillna(method='bfill')
print( df.iloc[360:370,] )
Out[122]:
0
t360 NaN
t361 NaN
t362 NaN
t363 NaN
t364 220.50
t365 228.59
t366 NaN
t367 NaN
t368 NaN
t369 NaN
When apply fillna() on sliced df, the NaN values could be replaced:
print( df.iloc[360:370,].fillna(method='bfill') )
0
t360 220.50
t361 220.50
t362 220.50
t363 220.50
t364 220.50
t365 228.59
t366 NaN
t367 NaN
t368 NaN
t369 NaN

Answer 1

You need assign output:
df = pd.read_excel('npp.xlsx')
df = df.fillna(method='bfill')
df = df[df[0].isnull()]
print (df)
Empty DataFrame
Columns: [0]
Index: []
Or use inplace=True parameter:
df = pd.read_excel('npp.xlsx')
df.fillna(method='bfill', inplace=True)
df = df[df[0].isnull()]
print (df)
Empty DataFrame
Columns: [0]
Index: []
Or shorter:
df = df.bfill()
df.bfill(inplace=True)