pandas.DataFrame.agg does not work with np.std?

Question

I am trying to use the pandas.DataFrame.agg function on the first column of a dataframe with the agg function is numpy.std .
I dont know why it works with numpy.mean but not numpy.std ?
Can someone tell me in what circumstance that happens.
This is very strange @@
The following describes what I am facing.

My source is like this:

print(type(dataframe))
print(dataframe.head(5))
first_col = dataframe.columns.values[0]
agg_df = dataframe.agg({first_col: [np.mean]})
print(agg_df)

then it shows the result like this

<class 'pandas.core.frame.DataFrame'>
        ax
0   -98.06
1   -97.81
2   -96.00
3   -93.44
4   -92.94

            ax
mean   -98.06

now I change the function from np.mean into np.std ( without changing anything else)

print(type(dataframe))
print(dataframe.head(5))
first_col = dataframe.columns.values[0]
agg_df = dataframe.agg({first_col: [np.std]})
print(agg_df)

it shows the errors

Traceback (most recent call last):
File "C:\prediction_framework_django\predictions\predictor.py", line 112, in pre_aggregated_unseen_data
    agg_df = dataframe.agg({axis: [np.std]})
File "C:\prediction_framework_django\env\lib\site-packages\pandas\core\frame.py", line 7578, in aggregate
    result, how = self._aggregate(func, axis, *args, **kwargs)
File "C:\prediction_framework_django\env\lib\site-packages\pandas\core\frame.py", line 7609, in _aggregate
    return aggregate(self, arg, *args, **kwargs)
File "C:\prediction_framework_django\env\lib\site-packages\pandas\core\aggregation.py", line 582, in aggregate
    return agg_dict_like(obj, arg, _axis), True
File "C:\prediction_framework_django\env\lib\site-packages\pandas\core\aggregation.py", line 768, in agg_dict_like
    results = {key: obj._gotitem(key, ndim=1).agg(how) for key, how in arg.items()}
File "C:\prediction_framework_django\env\lib\site-packages\pandas\core\aggregation.py", line 768, in <dictcomp>
    results = {key: obj._gotitem(key, ndim=1).agg(how) for key, how in arg.items()}
File "C:\prediction_framework_django\env\lib\site-packages\pandas\core\series.py", line 3974, in aggregate
    result, how = aggregate(self, func, *args, **kwargs)
File "C:\prediction_framework_django\env\lib\site-packages\pandas\core\aggregation.py", line 586, in aggregate
    return agg_list_like(obj, arg, _axis=_axis), None
File "C:\prediction_framework_django\env\lib\site-packages\pandas\core\aggregation.py", line 672, in agg_list_like
    raise ValueError("no results")
ValueError: no results

So the error is in agg_list_like raise ValueError("no results") ValueError: no results

Thank you for your time and help.

Answer 1

Simply use the pandas builtin:

# Note the use of string to denote the function here
df.agg({first_col: ['mean', 'std']})

# You can also simply use the following
df[first_col].mean()
df[first_col].std()

[EDIT]: The error that you are getting is probably resulting from mixed types. You can check that all dtypes are float by looking at df.dtypes . If you have one that is object , then convert the problematic ones (probably empty strings) into whatever you need and np.std and pandas' builtin std should work