I did this
cf = df.iloc[:,1:12]
cf = cf.values
print(cf)
which gives me
[['$0.00 ' '$771.98 ' '$0.00 ' ..., '$771.98 ' '$0.00 ' '$1,543.96 ']
['$1,320.83 ' '$4,782.33 ' '$1,320.83 ' ..., '$1,954.45 ' '$0.00 '
'$1,954.45 ']
['$2,043.61 ' '$0.00 ' '$4,087.22 ' ..., '$4,662.30 ' '$2,907.82 '
'$1,549.53 ']
...,
['$427.60 ' '$0.00 ' '$427.60 ' ..., '$427.60 ' '$0.00 ' '$427.60 ']
['$868.58 ' '$1,737.16 ' '$0.00 ' ..., '$868.58 ' '$868.58 ' '$868.58 ']
['$0.00 ' '$1,590.07 ' '$0.00 ' ..., '$787.75 ' '$0.00 ' '$0.00 ']]
I need these to be of floating types. This is not a possible duplicate since the cf variable is an NDarray not a data frame.
I tried doing this:
cf = df.iloc[:,1:12].replace('[\$,]', '', regex=True).astype(float)
cf = cf.values
print(cf)
But I get these errors:
ValueError Traceback (most recent call last)
<ipython-input-152-f5009cb31652> in <module>()
1 # Place as_of_date and cash flows into an unordered_map or dictionary
----> 2 cf = df.iloc[:,1:12].replace('[\$,]', '', regex=True).astype(float)
3 cf = cf.values
4 print(cf)
~\AppData\Local\Continuum\anaconda3\lib\site-packages\pandas\util\_decorators.py in wrapper(*args, **kwargs)
89 else:
90 kwargs[new_arg_name] = new_arg_value
---> 91 return func(*args, **kwargs)
92 return wrapper
93 return _deprecate_kwarg
~\AppData\Local\Continuum\anaconda3\lib\site-packages\pandas\core\generic.py in astype(self, dtype, copy, errors, **kwargs)
3408 # else, only a single dtype is given
3409 new_data = self._data.astype(dtype=dtype, copy=copy, errors=errors,
-> 3410 **kwargs)
3411 return self._constructor(new_data).__finalize__(self)
3412
~\AppData\Local\Continuum\anaconda3\lib\site-packages\pandas\core\internals.py in astype(self, dtype, **kwargs)
3222
3223 def astype(self, dtype, **kwargs):
-> 3224 return self.apply('astype', dtype=dtype, **kwargs)
3225
3226 def convert(self, **kwargs):
~\AppData\Local\Continuum\anaconda3\lib\site-packages\pandas\core\internals.py in apply(self, f, axes, filter, do_integrity_check, consolidate, **kwargs)
3089
3090 kwargs['mgr'] = self
-> 3091 applied = getattr(b, f)(**kwargs)
3092 result_blocks = _extend_blocks(applied, result_blocks)
3093
~\AppData\Local\Continuum\anaconda3\lib\site-packages\pandas\core\internals.py in astype(self, dtype, copy, errors, values, **kwargs)
469 def astype(self, dtype, copy=False, errors='raise', values=None, **kwargs):
470 return self._astype(dtype, copy=copy, errors=errors, values=values,
--> 471 **kwargs)
472
473 def _astype(self, dtype, copy=False, errors='raise', values=None,
~\AppData\Local\Continuum\anaconda3\lib\site-packages\pandas\core\internals.py in _astype(self, dtype, copy, errors, values, klass, mgr, raise_on_error, **kwargs)
519
520 # _astype_nansafe works fine with 1-d only
--> 521 values = astype_nansafe(values.ravel(), dtype, copy=True)
522 values = values.reshape(self.shape)
523
~\AppData\Local\Continuum\anaconda3\lib\site-packages\pandas\core\dtypes\cast.py in astype_nansafe(arr, dtype, copy)
634
635 if copy:
--> 636 return arr.astype(dtype)
637 return arr.view(dtype)
638
ValueError: could not convert string to float: '(641.99)'
I am not sure how to fix this, please revise answers so I can put this to rest and move on to something else.
From the suggested answer I did this
cf = df.iloc[:,1:12].replace('[^0-9]', '', regex=True).astype(float)
cf = cf.values
print(cf)
which gives me this
[[ 0. 77198. 0. ..., 77198. 0. 154396.]
[ 132083. 478233. 132083. ..., 195445. 0. 195445.]
[ 204361. 0. 408722. ..., 466230. 290782. 154953.]
...,
[ 42760. 0. 42760. ..., 42760. 0. 42760.]
[ 86858. 173716. 0. ..., 86858. 86858. 86858.]
[ 0. 159007. 0. ..., 78775. 0. 0.]]
The values are incorrect and need to be adjusted.
