Could someone tell me what non-printable character I have in my code that makes python not recognize the columns names in my dataframe? :
import pandas as pd
data_olymp = pd.read_csv("Olympics_data.csv", sep=";")
Here is the Traceback of the error when I try to group by teamname :
---------------------------------------------------------------------------
KeyError Traceback (most recent call last)
<ipython-input-103-ae95f10f5210> in <module>
30 # print(type(réponse1))
31 # print(len(winter_games_bronze_won))
---> 32 print(data_olymp.loc[" winter_games_bronze_won"] == 9)
~\anaconda3\lib\site-packages\pandas\core\indexing.py in __getitem__(self, key)
893
894 maybe_callable = com.apply_if_callable(key, self.obj)
--> 895 return self._getitem_axis(maybe_callable, axis=axis)
896
897 def _is_scalar_access(self, key: Tuple):
~\anaconda3\lib\site-packages\pandas\core\indexing.py in _getitem_axis(self, key, axis)
1122 # fall thru to straight lookup
1123 self._validate_key(key, axis)
-> 1124 return self._get_label(key, axis=axis)
1125
1126 def _get_slice_axis(self, slice_obj: slice, axis: int):
~\anaconda3\lib\site-packages\pandas\core\indexing.py in _get_label(self, label, axis)
1071 def _get_label(self, label, axis: int):
1072 # GH#5667 this will fail if the label is not present in the axis.
-> 1073 return self.obj.xs(label, axis=axis)
1074
1075 def _handle_lowerdim_multi_index_axis0(self, tup: Tuple):
~\anaconda3\lib\site-packages\pandas\core\generic.py in xs(self, key, axis, level, drop_level)
3737 raise TypeError(f"Expected label or tuple of labels, got {key}") from e
3738 else:
-> 3739 loc = index.get_loc(key)
3740
3741 if isinstance(loc, np.ndarray):
~\anaconda3\lib\site-packages\pandas\core\indexes\range.py in get_loc(self, key, method, tolerance)
352 except ValueError as err:
353 raise KeyError(key) from err
--> 354 raise KeyError(key)
355 return super().get_loc(key, method=method, tolerance=tolerance)
356
KeyError: ' winter_games_bronze_won'
The file looks like that :
team_name; summer_games_played; summer_games_gold_won; summer_games_silver_won; summer_games_bronze_won; summer_games_medals_won; winter_games_played; winter_games_gold_won; winter_games_silver_won; winter_games_bronze_won; winter_games_medals_won; total_games_played
Canada (CAN);13;0;0;2;2;0;0;0;0;0;13
United States (USA);12;5;2;8;15;3;0;0;0;0;15
Russia (RUS);23;18;24;28;70;18;0;0;0;0;41
Key errors are raised when you are trying to access a key that is not in a dictionary. While working Pandas, it is about the same thing. .loc is trying to locate a key value that is not found in the data frame.
Looking at your code and the traceback error, my assumption is that because you are trying to look up winter_games_bronze_won (with the spaces at the beginning), you are getting the error. Try removing the spaces before winter_games_bronze_won and see what happens.
Related
possibly a silly problem, but I'm stuck and I'd really appreciate someone's help. I'm trying to replicate the examples given in the walkthrough tutorial for trackpy (https://soft-matter.github.io/trackpy/dev/tutorial/walkthrough.html). I've been succesful up until I got to the point where I had to fit the ensemble mean-squared displacement to a power law (In [34]):
plt.figure()
plt.ylabel(r'$\langle \Delta r^2 \rangle$ [$\mu$m$^2$]')
plt.xlabel('lag time $t$');
tp.utils.fit_powerlaw(em) # performs linear best fit in log space, plots]
This is the error message I get. Can someone suggest a solution?
Thanks!
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
File ~/opt/anaconda3/lib/python3.9/site-packages/pandas/core/indexes/base.py:3621, in Index.get_loc(self, key, method, tolerance)
3620 try:
-> 3621 return self._engine.get_loc(casted_key)
3622 except KeyError as err:
File ~/opt/anaconda3/lib/python3.9/site-packages/pandas/_libs/index.pyx:136, in pandas._libs.index.IndexEngine.get_loc()
File ~/opt/anaconda3/lib/python3.9/site-packages/pandas/_libs/index.pyx:142, in pandas._libs.index.IndexEngine.get_loc()
TypeError: '(slice(None, None, None), None)' is an invalid key
During handling of the above exception, another exception occurred:
InvalidIndexError Traceback (most recent call last)
Input In [178], in <cell line: 4>()
2 plt.ylabel(r'$\langle \Delta r^2 \rangle$ [$\mu$m$^2$]')
3 plt.xlabel('lag time $t$');
----> 4 tp.utils.fit_powerlaw(em)
File ~/opt/anaconda3/lib/python3.9/site-packages/trackpy/utils.py:50, in fit_powerlaw(data, plot, **kwargs)
48 if plot:
49 from trackpy import plots
---> 50 plots.fit(data, fits, logx=True, logy=True, legend=False, **kwargs)
51 return values
File ~/opt/anaconda3/lib/python3.9/site-packages/trackpy/plots.py:50, in make_axes.<locals>.wrapper(*args, **kwargs)
47 # Delete legend keyword so remaining ones can be passed to plot().
48 legend = kwargs.pop('legend', False)
---> 50 result = func(*args, **kwargs)
52 if legend:
53 handles, labels = kwargs['ax'].get_legend_handles_labels()
File ~/opt/anaconda3/lib/python3.9/site-packages/trackpy/plots.py:652, in fit(data, fits, inverted_model, logx, logy, ax, **kwargs)
650 ax.set_yscale('log')
651 if not inverted_model:
--> 652 fitlines = ax.plot(fits.index, fits, **kwargs)
653 else:
654 fitlines = ax.plot(fits.reindex(data.dropna().index),
655 data.dropna(), **kwargs)
File ~/opt/anaconda3/lib/python3.9/site-packages/matplotlib/axes/_axes.py:1632, in Axes.plot(self, scalex, scaley, data, *args, **kwargs)
1390 """
1391 Plot y versus x as lines and/or markers.
1392
(...)
1629 (``'green'``) or hex strings (``'#008000'``).
1630 """
1631 kwargs = cbook.normalize_kwargs(kwargs, mlines.Line2D)
-> 1632 lines = [*self._get_lines(*args, data=data, **kwargs)]
1633 for line in lines:
1634 self.add_line(line)
File ~/opt/anaconda3/lib/python3.9/site-packages/matplotlib/axes/_base.py:312, in _process_plot_var_args.__call__(self, data, *args, **kwargs)
310 this += args[0],
311 args = args[1:]
--> 312 yield from self._plot_args(this, kwargs)
File ~/opt/anaconda3/lib/python3.9/site-packages/matplotlib/axes/_base.py:488, in _process_plot_var_args._plot_args(self, tup, kwargs, return_kwargs)
486 if len(xy) == 2:
487 x = _check_1d(xy[0])
--> 488 y = _check_1d(xy[1])
489 else:
490 x, y = index_of(xy[-1])
File ~/opt/anaconda3/lib/python3.9/site-packages/matplotlib/cbook/__init__.py:1327, in _check_1d(x)
1321 with warnings.catch_warnings(record=True) as w:
1322 warnings.filterwarnings(
1323 "always",
1324 category=Warning,
1325 message='Support for multi-dimensional indexing')
-> 1327 ndim = x[:, None].ndim
1328 # we have definitely hit a pandas index or series object
1329 # cast to a numpy array.
1330 if len(w) > 0:
File ~/opt/anaconda3/lib/python3.9/site-packages/pandas/core/frame.py:3505, in DataFrame.__getitem__(self, key)
3503 if self.columns.nlevels > 1:
3504 return self._getitem_multilevel(key)
-> 3505 indexer = self.columns.get_loc(key)
3506 if is_integer(indexer):
3507 indexer = [indexer]
File ~/opt/anaconda3/lib/python3.9/site-packages/pandas/core/indexes/base.py:3628, in Index.get_loc(self, key, method, tolerance)
3623 raise KeyError(key) from err
3624 except TypeError:
3625 # If we have a listlike key, _check_indexing_error will raise
3626 # InvalidIndexError. Otherwise we fall through and re-raise
3627 # the TypeError.
-> 3628 self._check_indexing_error(key)
3629 raise
3631 # GH#42269
File ~/opt/anaconda3/lib/python3.9/site-packages/pandas/core/indexes/base.py:5637, in Index._check_indexing_error(self, key)
5633 def _check_indexing_error(self, key):
5634 if not is_scalar(key):
5635 # if key is not a scalar, directly raise an error (the code below
5636 # would convert to numpy arrays and raise later any way) - GH29926
-> 5637 raise InvalidIndexError(key)
InvalidIndexError: (slice(None, None, None), None)
Currently if i run some error code in IPython with Pandas, for example, a script named temp.py
import pandas as pd
temp = pd.Series(range(5))
print(temp.loc[6])
then run command %run temp.py in IPython console, I get some error info like
KeyError Traceback (most recent call last)
D:\codes\python\test.py in <module>
2
3 temp = pd.Series(range(5))
----> 4 print(temp.loc[6])
C:\ProgramData\Anaconda3\lib\site-packages\pandas\core\indexing.py in __getitem__(self, key)
929
930 maybe_callable = com.apply_if_callable(key, self.obj)
--> 931 return self._getitem_axis(maybe_callable, axis=axis)
932
933 def _is_scalar_access(self, key: tuple):
C:\ProgramData\Anaconda3\lib\site-packages\pandas\core\indexing.py in _getitem_axis(self, key, axis)
1162 # fall thru to straight lookup
1163 self._validate_key(key, axis)
-> 1164 return self._get_label(key, axis=axis)
1165
1166 def _get_slice_axis(self, slice_obj: slice, axis: int):
C:\ProgramData\Anaconda3\lib\site-packages\pandas\core\indexing.py in _get_label(self, label, axis)
1111 def _get_label(self, label, axis: int):
1112 # GH#5667 this will fail if the label is not present in the axis.
-> 1113 return self.obj.xs(label, axis=axis)
1114
1115 def _handle_lowerdim_multi_index_axis0(self, tup: tuple):
C:\ProgramData\Anaconda3\lib\site-packages\pandas\core\generic.py in xs(self, key, axis, level, drop_level)
3774 raise TypeError(f"Expected label or tuple of labels, got {key}") from e
3775 else:
-> 3776 loc = index.get_loc(key)
3777
3778 if isinstance(loc, np.ndarray):
C:\ProgramData\Anaconda3\lib\site-packages\pandas\core\indexes\range.py in get_loc(self, key, method, tolerance)
385 return self._range.index(new_key)
386 except ValueError as err:
--> 387 raise KeyError(key) from err
388 raise KeyError(key)
389 return super().get_loc(key, method=method, tolerance=tolerance)
KeyError: 6
the error info here is too long and useless, if I want to get the error code of my own, I need to scroll up to find what is the error place of my own.
Also after that when I run %debug command, I also got into the pandas function and local vars instead of my own code.
So is there a way to make IPython show error info and debug just in my own code?
I think my issue is that not every file i am analysing contains every item in my sleep_stages list but I'm not sure how to fix it. For instance some files will not contain any mention of sleep stage N1 or another item from list. I would like to be able to input na just for that value but capture other values from items on list.
see code:
def get_sleep_times(hypno):
sleep_stages=['Sleep stage N1','Sleep stage R','Sleep stage N2', 'Sleep
stage N3', 'Sleep stage ?']
sleep_times = {}
totsleep_time = 0
tmp = hypno.groupby('description')['duration'].sum()
for stage in sleep_stages:
sleep_times['Duration of ' +stage]=tmp.loc[stage]
totsleep_time += tmp.loc[stage]
sleep_times['Total Sleep Duration'] = totsleep_time
return sleep_times
see error message:
KeyError Traceback (most recent call last)
~\Anaconda3\lib\site-packages\pandas\core\indexes\base.py in get_loc(self, key, method, tolerance)
3360 try:
-> 3361 return self._engine.get_loc(casted_key)
3362 except KeyError as err:
~\Anaconda3\lib\site-packages\pandas\_libs\index.pyx in pandas._libs.index.IndexEngine.get_loc()
~\Anaconda3\lib\site-packages\pandas\_libs\index.pyx in pandas._libs.index.IndexEngine.get_loc()
pandas\_libs\hashtable_class_helper.pxi in pandas._libs.hashtable.PyObjectHashTable.get_item()
pandas\_libs\hashtable_class_helper.pxi in pandas._libs.hashtable.PyObjectHashTable.get_item()
KeyError: 'Sleep stage ?'
The above exception was the direct cause of the following exception:
KeyError Traceback (most recent call last)
~\AppData\Local\Temp/ipykernel_21360/487801242.py in <module>
----> 1 hypno_report(dfpmnospcl)
~\AppData\Local\Temp/ipykernel_21360/1936770717.py in hypno_report(df)
16 print(fnames, matches)
17 hypno = pd.read_csv(matches[0], delimiter='\t',encoding='utf-8')
---> 18 result.update(get_sleep_times(hypno))
19 result.update(get_hypno_counts(hypno, events))
20 results.append(result)
~\AppData\Local\Temp/ipykernel_21360/2297364264.py in get_sleep_times(hypno)
12
13 else:
---> 14 sleep_times['Duration of ' +stage]=tmp.loc[stage]
15 totsleep_time += tmp.loc[stage]
16
~\Anaconda3\lib\site-packages\pandas\core\indexing.py in __getitem__(self, key)
929
930 maybe_callable = com.apply_if_callable(key, self.obj)
--> 931 return self._getitem_axis(maybe_callable, axis=axis)
932
933 def _is_scalar_access(self, key: tuple):
~\Anaconda3\lib\site-packages\pandas\core\indexing.py in _getitem_axis(self, key, axis)
1162 # fall thru to straight lookup
1163 self._validate_key(key, axis)
-> 1164 return self._get_label(key, axis=axis)
1165
1166 def _get_slice_axis(self, slice_obj: slice, axis: int):
~\Anaconda3\lib\site-packages\pandas\core\indexing.py in _get_label(self, label, axis)
1111 def _get_label(self, label, axis: int):
1112 # GH#5667 this will fail if the label is not present in the axis.
-> 1113 return self.obj.xs(label, axis=axis)
1114
1115 def _handle_lowerdim_multi_index_axis0(self, tup: tuple):
~\Anaconda3\lib\site-packages\pandas\core\generic.py in xs(self, key, axis, level, drop_level)
3774 raise TypeError(f"Expected label or tuple of labels, got {key}") from e
3775 else:
-> 3776 loc = index.get_loc(key)
3777
3778 if isinstance(loc, np.ndarray):
~\Anaconda3\lib\site-packages\pandas\core\indexes\base.py in get_loc(self, key, method, tolerance)
3361 return self._engine.get_loc(casted_key)
3362 except KeyError as err:
-> 3363 raise KeyError(key) from err
3364
3365 if is_scalar(key) and isna(key) and not self.hasnans:
KeyError: 'Sleep stage ?'
This might not work properly since I don't know how hypno looks like. Would be helpful if you could describe its structure next time.
def get_sleep_times(hypno):
sleep_stages=['Sleep stage N1', 'Sleep stage R', 'Sleep stage N2', 'Sleep stage N3', 'Sleep stage ?']
tmp = hypno.groupby('description')['duration'].sum()
sleep_times = {'Duration of ' + stage: tmp.loc[stage] if stage in tmp.columns else None for stage in sleep_stages}
sleep_times['Total sleep duration: '] = sum(sleep_times.values())
return sleep_times
The sleep_times dictionary will contain the duration for each stage (if the stage name is present within the column names of tmp) or None otherwise.
The values from the dictionary will then be summed up and added as a new entry (total sleep duration).
I have a dataframe where I am trying to create a new column based on applying a lambda to two existing columns. The dataframe uses a datetimeindex and each column is either float or int and there are no missing or null values:
closeunadj qtr_timedelta
date
2021-05-18 128.75 107
2021-05-19 130.21 108
2021-05-20 132.15 109
2021-05-21 132.30 110
2021-05-24 133.34 113
<class 'pandas.core.frame.DataFrame'>
DatetimeIndex: 1021 entries, 2017-05-01 to 2021-05-24
Data columns (total 2 columns):
# Column Non-Null Count Dtype
--- ------ -------------- -----
0 closeunadj 1021 non-null float64
1 qtr_timedelta 1021 non-null int64
dtypes: float64(1), int64(1)
memory usage: 63.9 KB
The lambda calculates a simple shifted return on the first column using a changing shift count value from the second column.
final_merge['qtr_gwth'] = final_merge[['closeunadj',
'qtr_timedelta']].apply(lambda x: x['closeunadj'] / x['closeunadj'].shift(x['qtr_timedelta']) - 1)
However, I get the following errors (in traceback order) which don’t make sense to me since the dataframe values are either datetimeindex, float, or int (as outlined above). ‘closeunadj’ is float64, index is datetimeindex, and there are no str objects.
TypeError: 'str' object cannot be interpreted as an integer
KeyError: 'closeunadj'
ParserError: Unknown string format: closeunadj
ValueError: could not convert string to Timestamp
KeyError: ‘closeunadj'
I have tried recasting the columns to float and int, recasting the datetimeindex, recreating the dataframe and using a different lambda syntax, all to no avail. Any help or fix greatly appreciated!
This is the full traceback:
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
~/opt/anaconda3/lib/python3.8/site-packages/pandas/core/indexes/base.py in get_value(self, series, key)
4410 try:
-> 4411 return libindex.get_value_at(s, key)
4412 except IndexError:
pandas/_libs/index.pyx in pandas._libs.index.get_value_at()
pandas/_libs/index.pyx in pandas._libs.index.get_value_at()
pandas/_libs/util.pxd in pandas._libs.util.get_value_at()
pandas/_libs/util.pxd in pandas._libs.util.validate_indexer()
TypeError: 'str' object cannot be interpreted as an integer
During handling of the above exception, another exception occurred:
KeyError Traceback (most recent call last)
~/opt/anaconda3/lib/python3.8/site-packages/pandas/core/indexes/datetimes.py in get_value(self, series, key)
650 try:
--> 651 value = Index.get_value(self, series, key)
652 except KeyError:
~/opt/anaconda3/lib/python3.8/site-packages/pandas/core/indexes/base.py in get_value(self, series, key)
4418 else:
-> 4419 raise e1
4420 except Exception:
~/opt/anaconda3/lib/python3.8/site-packages/pandas/core/indexes/base.py in get_value(self, series, key)
4404 try:
-> 4405 return self._engine.get_value(s, k, tz=getattr(series.dtype, "tz", None))
4406 except KeyError as e1:
pandas/_libs/index.pyx in pandas._libs.index.IndexEngine.get_value()
pandas/_libs/index.pyx in pandas._libs.index.IndexEngine.get_value()
pandas/_libs/index.pyx in pandas._libs.index.DatetimeEngine.get_loc()
pandas/_libs/index.pyx in pandas._libs.index.DatetimeEngine._date_check_type()
KeyError: 'closeunadj'
During handling of the above exception, another exception occurred:
ParserError Traceback (most recent call last)
pandas/_libs/tslibs/conversion.pyx in pandas._libs.tslibs.conversion.convert_str_to_tsobject()
pandas/_libs/tslibs/parsing.pyx in pandas._libs.tslibs.parsing.parse_datetime_string()
~/opt/anaconda3/lib/python3.8/site-packages/dateutil/parser/_parser.py in parse(timestr, parserinfo, **kwargs)
1373 else:
-> 1374 return DEFAULTPARSER.parse(timestr, **kwargs)
1375
~/opt/anaconda3/lib/python3.8/site-packages/dateutil/parser/_parser.py in parse(self, timestr, default, ignoretz, tzinfos, **kwargs)
648 if res is None:
--> 649 raise ParserError("Unknown string format: %s", timestr)
650
ParserError: Unknown string format: closeunadj
During handling of the above exception, another exception occurred:
ValueError Traceback (most recent call last)
~/opt/anaconda3/lib/python3.8/site-packages/pandas/core/indexes/datetimes.py in get_value(self, series, key)
659 try:
--> 660 return self.get_value_maybe_box(series, key)
661 except (TypeError, ValueError, KeyError):
~/opt/anaconda3/lib/python3.8/site-packages/pandas/core/indexes/datetimes.py in get_value_maybe_box(self, series, key)
674 elif not isinstance(key, Timestamp):
--> 675 key = Timestamp(key)
676 values = self._engine.get_value(com.values_from_object(series), key, tz=self.tz)
pandas/_libs/tslibs/timestamps.pyx in pandas._libs.tslibs.timestamps.Timestamp.__new__()
pandas/_libs/tslibs/conversion.pyx in pandas._libs.tslibs.conversion.convert_to_tsobject()
pandas/_libs/tslibs/conversion.pyx in pandas._libs.tslibs.conversion.convert_str_to_tsobject()
ValueError: could not convert string to Timestamp
During handling of the above exception, another exception occurred:
KeyError Traceback (most recent call last)
<ipython-input-55-ac0ccaa452bc> in <module>
1 # Use close price change from date of last results
----> 2 final_merge['qtr_gwth'] = final_merge[['closeunadj',
3 'qtr_timedelta']].apply(lambda x : x['closeunadj'] / x['closeunadj'].shift(x['qtr_timedelta']) - 1)
4
~/opt/anaconda3/lib/python3.8/site-packages/pandas/core/frame.py in apply(self, func, axis, raw, result_type, args, **kwds)
6876 kwds=kwds,
6877 )
-> 6878 return op.get_result()
6879
6880 def applymap(self, func) -> "DataFrame":
~/opt/anaconda3/lib/python3.8/site-packages/pandas/core/apply.py in get_result(self)
184 return self.apply_raw()
185
--> 186 return self.apply_standard()
187
188 def apply_empty_result(self):
~/opt/anaconda3/lib/python3.8/site-packages/pandas/core/apply.py in apply_standard(self)
293
294 try:
--> 295 result = libreduction.compute_reduction(
296 values, self.f, axis=self.axis, dummy=dummy, labels=labels
297 )
pandas/_libs/reduction.pyx in pandas._libs.reduction.compute_reduction()
pandas/_libs/reduction.pyx in pandas._libs.reduction.Reducer.get_result()
<ipython-input-55-ac0ccaa452bc> in <lambda>(x)
1 # Use close price change from date of last results
2 final_merge['qtr_gwth'] = final_merge[['closeunadj',
----> 3 'qtr_timedelta']].apply(lambda x : x['closeunadj'] / x['closeunadj'].shift(x['qtr_timedelta']) - 1)
4
~/opt/anaconda3/lib/python3.8/site-packages/pandas/core/series.py in __getitem__(self, key)
869 key = com.apply_if_callable(key, self)
870 try:
--> 871 result = self.index.get_value(self, key)
872
873 if not is_scalar(result):
~/opt/anaconda3/lib/python3.8/site-packages/pandas/core/indexes/datetimes.py in get_value(self, series, key)
660 return self.get_value_maybe_box(series, key)
661 except (TypeError, ValueError, KeyError):
--> 662 raise KeyError(key)
663 else:
664 return com.maybe_box(self, value, series, key)
KeyError: 'closeunadj'
I have 400 columns and I am trying to do min-max normalization (row-wise). For the first 200 points I want to do min-max normalization and scale it between 0 and 500 and do the same for the next two hundred points but scale it between 0 and 10.
import pandas as pd
import numpy as np
df = pd.DataFrame(np.random.randint(500,1000,size=(5, 400)))
def normalize(ds,value):
normalizedds = []
normalizedds.extend((ds[:value] - np.min(ds[:value])) / np.max(ds[:value] - np.min(ds[:value])) * 500)
normalizedds.extend(ds[value:value*2] / np.max(ds[value:value*2]) * 10)
return normalizedds
normalizeddsList = pd.DataFrame.from_records(df.apply(normalize, value=200, axis=1))
I get the following error!
ValueError Traceback (most recent call last)
~\AppData\Roaming\Python\Python37\site-packages\pandas\core\indexes\base.py in get_slice_bound(self, label, side, kind)
5166 try:
-> 5167 return self._searchsorted_monotonic(label, side)
5168 except ValueError:
~\AppData\Roaming\Python\Python37\site-packages\pandas\core\indexes\base.py in _searchsorted_monotonic(self, label, side)
5127
-> 5128 raise ValueError("index must be monotonic increasing or decreasing")
5129
ValueError: index must be monotonic increasing or decreasing
During handling of the above exception, another exception occurred:
KeyError Traceback (most recent call last)
in
----> 1 scaledCardList = pd.DataFrame.from_records(originalCardList.apply(scale, pointCount=200, axis=1))
~\AppData\Roaming\Python\Python37\site-packages\pandas\core\frame.py in apply(self, func, axis, broadcast, raw, reduce, result_type, args, **kwds)
6926 kwds=kwds,
6927 )
-> 6928 return op.get_result()
6929
6930 def applymap(self, func):
~\AppData\Roaming\Python\Python37\site-packages\pandas\core\apply.py in get_result(self)
184 return self.apply_raw()
185
--> 186 return self.apply_standard()
187
188 def apply_empty_result(self):
~\AppData\Roaming\Python\Python37\site-packages\pandas\core\apply.py in apply_standard(self)
290
291 # compute the result using the series generator
--> 292 self.apply_series_generator()
293
294 # wrap results
~\AppData\Roaming\Python\Python37\site-packages\pandas\core\apply.py in apply_series_generator(self)
319 try:
320 for i, v in enumerate(series_gen):
--> 321 results[i] = self.f(v)
322 keys.append(v.name)
323 except Exception as e:
~\AppData\Roaming\Python\Python37\site-packages\pandas\core\apply.py in f(x)
110
111 def f(x):
--> 112 return func(x, *args, **kwds)
113
114 else:
in scale(card, pointCount)
1 def scale(card, pointCount):
2 scaledCard = []
----> 3 scaledCard.extend((card[:pointCount] - np.min(card[:pointCount])) / np.max(card[:pointCount] - np.min(card[:pointCount])) * 10000)
4 scaledCard.extend(card[pointCount:pointCount*2] / np.max(card[pointCount:pointCount*2]) * 100)
5 return scaledCard
~\AppData\Roaming\Python\Python37\site-packages\pandas\core\series.py in getitem(self, key)
1111 key = check_bool_indexer(self.index, key)
1112
-> 1113 return self._get_with(key)
1114
1115 def _get_with(self, key):
~\AppData\Roaming\Python\Python37\site-packages\pandas\core\series.py in _get_with(self, key)
1116 # other: fancy integer or otherwise
1117 if isinstance(key, slice):
-> 1118 indexer = self.index._convert_slice_indexer(key, kind="getitem")
1119 return self._get_values(indexer)
1120 elif isinstance(key, ABCDataFrame):
~\AppData\Roaming\Python\Python37\site-packages\pandas\core\indexes\numeric.py in _convert_slice_indexer(self, key, kind)
395
396 # translate to locations
--> 397 return self.slice_indexer(key.start, key.stop, key.step, kind=kind)
398
399 def _format_native_types(
~\AppData\Roaming\Python\Python37\site-packages\pandas\core\indexes\base.py in slice_indexer(self, start, end, step, kind)
5032 slice(1, 3)
5033 """
-> 5034 start_slice, end_slice = self.slice_locs(start, end, step=step, kind=kind)
5035
5036 # return a slice
~\AppData\Roaming\Python\Python37\site-packages\pandas\core\indexes\base.py in slice_locs(self, start, end, step, kind)
5252 end_slice = None
5253 if end is not None:
-> 5254 end_slice = self.get_slice_bound(end, "right", kind)
5255 if end_slice is None:
5256 end_slice = len(self)
~\AppData\Roaming\Python\Python37\site-packages\pandas\core\indexes\base.py in get_slice_bound(self, label, side, kind)
5168 except ValueError:
5169 # raise the original KeyError
-> 5170 raise err
5171
5172 if isinstance(slc, np.ndarray):
~\AppData\Roaming\Python\Python37\site-packages\pandas\core\indexes\base.py in get_slice_bound(self, label, side, kind)
5162 # we need to look up the label
5163 try:
-> 5164 slc = self.get_loc(label)
5165 except KeyError as err:
5166 try:
~\AppData\Roaming\Python\Python37\site-packages\pandas\core\indexes\numeric.py in get_loc(self, key, method, tolerance)
477 except (TypeError, NotImplementedError):
478 pass
--> 479 return super().get_loc(key, method=method, tolerance=tolerance)
480
481 #cache_readonly
~\AppData\Roaming\Python\Python37\site-packages\pandas\core\indexes\base.py in get_loc(self, key, method, tolerance)
2897 return self._engine.get_loc(key)
2898 except KeyError:
-> 2899 return self._engine.get_loc(self._maybe_cast_indexer(key))
2900 indexer = self.get_indexer([key], method=method, tolerance=tolerance)
2901 if indexer.ndim > 1 or indexer.size > 1:
pandas/_libs/index.pyx in pandas._libs.index.IndexEngine.get_loc()
pandas/_libs/index.pyx in pandas._libs.index.IndexEngine.get_loc()
pandas/_libs/hashtable_class_helper.pxi in pandas._libs.hashtable.Float64HashTable.get_item()
pandas/_libs/hashtable_class_helper.pxi in pandas._libs.hashtable.Float64HashTable.get_item()
KeyError: (200.0, 'occurred at index 0')