How to get the max/min value in Pandas DataFrame when nan value in it

Question

Since one column of my pandas dataframe has nan value, so when I want to get the max value of that column, it just return error.

>>> d         


        

Answer 1

You can use NumPy's help with np.nanmax, np.nanmin :

In [28]: df
Out[28]: 
   A   B  C
0  7 NaN  8
1  3   3  5
2  8   1  7
3  3   0  3
4  8   2  7

In [29]: np.nanmax(df.iloc[:, 1].values)
Out[29]: 3.0

In [30]: np.nanmin(df.iloc[:, 1].values)
Out[30]: 0.0

Answer 2

You can use Series.dropna.

res = df.iloc[:, 1].dropna().max()

Answer 3

When the df contains NaN values it reports NaN values, Using np.nanmax(df.values) gave the desired answer.

Answer 4

Dataframe aggregate function.agg() will automatically ignore NaN value. df.agg({'income':'max'})

Besides, it can also be use together with .groupby

df.groupby('column').agg({'income':['max','mean']})

Answer 5

You can set numeric_only = True when calling max:

df.iloc[:, 1].max(numeric_only = True)

Answer 6

if you dont use iloc or loc, it is simple as:

df['column'].max()

or

df['column'][df.index.min():df.index.max()]

or any kind of range in this second square brackets