--------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
<ipython-input-4-c5cf824082a8> in <module>
      1 with pandas_log.enable():
      2     df = (
----> 3         pd.merge(df_a,df_b,on='b')
      4     )

~\.conda\envs\empl\lib\site-packages\pandas\core\reshape\merge.py in merge(left, right, how, on, left_on, right_on, left_index, right_index, sort, suffixes, copy, indicator, validate)
     79         copy=copy,
     80         indicator=indicator,
---> 81         validate=validate,
     82     )
     83     return op.get_result()

~\.conda\envs\empl\lib\site-packages\pandas\core\reshape\merge.py in __init__(self, left, right, how, on, left_on, right_on, axis, left_index, right_index, sort, suffixes, copy, indicator, validate)
    624             self.right_join_keys,
    625             self.join_names,
--> 626         ) = self._get_merge_keys()
    627 
    628         # validate the merge keys dtypes. We may need to coerce

~\.conda\envs\empl\lib\site-packages\pandas\core\reshape\merge.py in _get_merge_keys(self)
   1031 
   1032         if right_drop:
-> 1033             self.right = self.right._drop_labels_or_levels(right_drop)
   1034 
   1035         return left_keys, right_keys, join_names

~\.conda\envs\empl\lib\site-packages\pandas\core\generic.py in _drop_labels_or_levels(self, keys, axis)
   1860             # Handle dropping columns labels
   1861             if labels_to_drop:
-> 1862                 dropped.drop(labels_to_drop, axis=1, inplace=True)
   1863         else:
   1864             # Handle dropping column levels

~\.conda\envs\empl\lib\site-packages\pandas_flavor\register.py in __call__(self, *args, **kwargs)
     27             @wraps(method)
     28             def __call__(self, *args, **kwargs):
---> 29                 return method(self._obj, *args, **kwargs)
     30 
     31         register_dataframe_accessor(method.__name__)(AccessorMethod)

~\.conda\envs\empl\lib\site-packages\pandas_log\pandas_log.py in wrapped(*args, **fn_kwargs)
    134                 full_signature,
    135                 silent,
--> 136                 verbose,
    137             )
    138             return output_df

~\.conda\envs\empl\lib\site-packages\pandas_log\pandas_log.py in _run_method_and_calc_stats(fn, fn_args, fn_kwargs, input_df, full_signature, silent, verbose)
    104 
    105         output_df, execution_stats = get_execution_stats(
--> 106             fn, input_df, fn_args, fn_kwargs
    107         )
    108 

~\.conda\envs\empl\lib\site-packages\pandas_log\pandas_execution_stats.py in get_execution_stats(fn, input_df, fn_args, fn_kwargs)
     35 
     36     input_memory_size = StepStats.calc_df_series_memory(input_df)
---> 37     output_memory_size = StepStats.calc_df_series_memory(output_df)
     38 
     39     ExecutionStats = namedtuple(

~\.conda\envs\empl\lib\site-packages\pandas_log\pandas_execution_stats.py in calc_df_series_memory(df_or_series)
     78     @staticmethod
     79     def calc_df_series_memory(df_or_series):
---> 80         memory_size = df_or_series.memory_usage(index=True, deep=True)
     81         return (
     82             humanize.naturalsize(memory_size.sum())

AttributeError: 'NoneType' object has no attribute 'memory_usage'

--> 114             import pandas_log
    115 
    116             with pandas_logs.enable():

~/GitHub/simple-tech-challenges/venv/lib/python3.8/site-packages/pandas_log/__init__.py in <module>
      2 
      3 """Top-level package for pandas-log."""
----> 4 from .pandas_log import *
      5 
      6 __author__ = """Eyal Trabelsi"""

~/GitHub/simple-tech-challenges/venv/lib/python3.8/site-packages/pandas_log/pandas_log.py in <module>
     15     restore_pandas_func_copy,
     16 )
---> 17 from pandas_log.pandas_execution_stats import StepStats, get_execution_stats
     18 
     19 __all__ = ["auto_enable", "auto_disable", "enable"]

~/GitHub/simple-tech-challenges/venv/lib/python3.8/site-packages/pandas_log/pandas_execution_stats.py in <module>
     22 with warnings.catch_warnings():
     23     warnings.simplefilter("ignore")
---> 24     import humanize
     25 
     26 

ModuleNotFoundError: No module named 'humanize'

with enable():
    df = pd.read_csv("../examples/pokemon.csv")
    (
        df.query("legendary==0")
        .query("type_1=='fire' or type_2=='fire'")
    )
df.query("legendary==1")

TypeError: data type not understood

import pandas as pd
autos = pd.read_csv('https://github.com/mattharrison/datasets/raw/master/data/vehicles.csv.zip')
def to_tz(df_, time_col, tz_offset, tz_name):
    return (df_
             .groupby(tz_offset)
             [time_col]
             .transform(lambda s: pd.to_datetime(s)
                 .dt.tz_localize(s.name, ambiguous=True)
                 .dt.tz_convert(tz_name))
            )


def tweak_autos(autos):
    cols = ['city08', 'comb08', 'highway08', 'cylinders', 'displ', 'drive', 'eng_dscr', 
        'fuelCost08', 'make', 'model', 'trany', 'range', 'createdOn', 'year']
    return (autos
     [cols]
     .assign(cylinders=autos.cylinders.fillna(0).astype('int8'),
             displ=autos.displ.fillna(0).astype('float16'),
             drive=autos.drive.fillna('Other').astype('category'),
             automatic=autos.trany.str.contains('Auto'),
             speeds=autos.trany.str.extract(r'(\d)+').fillna('20').astype('int8'),
             tz=autos.createdOn.str.extract(r'\d\d:\d\d ([A-Z]{3}?)').replace('EDT', 'EST5EDT'),
             str_date=(autos.createdOn.str.slice(4,19) + ' ' + autos.createdOn.str.slice(-4)),
             createdOn=lambda df_: to_tz(df_, 'str_date', 'tz', 'US/Eastern'),
             ffs=autos.eng_dscr.str.contains('FFS')
            )
     .pipe(show, rows=2, title='New Cols')            
     .astype({'highway08': 'int8', 'city08': 'int16', 'comb08': 'int16', 'fuelCost08': 'int16',
              'range': 'int16',  'year': 'int16', 'make': 'category'})
     .drop(columns=['trany', 'eng_dscr'])
    )
import pandas_log
with pandas_log.enable():
    tweak_autos(autos)

1) fillna(value: 'object | ArrayLike | None' ="20", method: 'FillnaOptions | None' = None, axis: 'Axis | None' = None, inplace: 'bool' = False, limit=None, downcast=None):
	Metadata:
	* Filled 837 with 20.
	Execution Stats:
	* Execution time: Step Took 0.001512 seconds.

1) replace(to_replace="EDT", value="EST5EDT", inplace: 'bool' = False, limit=None, regex: 'bool' = False, method: 'str' = 'pad'):
	Execution Stats:
	* Execution time: Step Took 0.001215 seconds.

1) groupby(by="tz", axis: 'Axis' = 0, level: 'Level | None' = None, as_index: 'bool' = True, sort: 'bool' = True, group_keys: 'bool' = True, squeeze: 'bool | lib.NoDefault' = <no_default>, observed: 'bool' = False, dropna: 'bool' = True):
	Metadata:
	* Grouping by tz resulted in 2 groups like 
		EST,
		EST5EDT,
	  and more.
	Execution Stats:
	* Execution time: Step Took 0.006409 seconds.
/home/matt/envs/menv/lib/python3.8/site-packages/pandas_log/patched_logs_functions.py:249: UserWarning: Some pandas logging may involve copying dataframes, which can be time-/memory-intensive. Consider passing copy_ok=False to the enable/auto_enable functions in pandas_log if issues arise.
  warnings.warn(COPY_WARNING_MSG)
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-1-f6bfc55c635b> in <module>
     33 import pandas_log
     34 with pandas_log.enable():
---> 35     tweak_autos(autos)

<ipython-input-1-f6bfc55c635b> in tweak_autos(autos)
     14     cols = ['city08', 'comb08', 'highway08', 'cylinders', 'displ', 'drive', 'eng_dscr', 
     15         'fuelCost08', 'make', 'model', 'trany', 'range', 'createdOn', 'year']
---> 16     return (autos
     17      [cols]
     18      .assign(cylinders=autos.cylinders.fillna(0).astype('int8'),

~/envs/menv/lib/python3.8/site-packages/pandas_flavor/register.py in __call__(self, *args, **kwargs)
     27             @wraps(method)
     28             def __call__(self, *args, **kwargs):
---> 29                 return method(self._obj, *args, **kwargs)
     30 
     31         register_dataframe_accessor(method.__name__)(AccessorMethod)

~/envs/menv/lib/python3.8/site-packages/pandas_log/pandas_log.py in wrapped(*args, **fn_kwargs)
    184 
    185             input_df, fn_args = args[0], args[1:]
--> 186             output_df = _run_method_and_calc_stats(
    187                 fn,
    188                 fn_args,

~/envs/menv/lib/python3.8/site-packages/pandas_log/pandas_log.py in _run_method_and_calc_stats(fn, fn_args, fn_kwargs, input_df, full_signature, silent, verbose, copy_ok, calculate_memory)
    168             output_df,
    169         )
--> 170         step_stats.log_stats_if_needed(silent, verbose, copy_ok)
    171         if isinstance(output_df, pd.DataFrame) or isinstance(output_df, pd.Series):
    172             step_stats.persist_execution_stats()

~/envs/menv/lib/python3.8/site-packages/pandas_log/pandas_execution_stats.py in log_stats_if_needed(self, silent, verbose, copy_ok)
    106 
    107         if verbose or self.fn.__name__ not in DATAFRAME_ADDITIONAL_METHODS_TO_OVERIDE:
--> 108             s = self.__repr__(verbose, copy_ok)
    109             if s:
    110                 # If this method isn't patched and verbose is False, __repr__ will give an empty string, which

~/envs/menv/lib/python3.8/site-packages/pandas_log/pandas_execution_stats.py in __repr__(self, verbose, copy_ok)
    147 
    148         # Step Metadata stats
--> 149         logs, tips = self.get_logs_for_specifc_method(verbose, copy_ok)
    150         metadata_stats = f"\033[4mMetadata\033[0m:\n{logs}" if logs else ""
    151         metadata_tips = f"\033[4mTips\033[0m:\n{tips}" if tips else ""

~/envs/menv/lib/python3.8/site-packages/pandas_log/pandas_execution_stats.py in get_logs_for_specifc_method(self, verbose, copy_ok)
    128 
    129         log_method = partial(log_method, self.output_df, self.input_df)
--> 130         logs, tips = log_method(*self.fn_args, **self.fn_kwargs)
    131         return logs, tips
    132 

~/envs/menv/lib/python3.8/site-packages/pandas_log/patched_logs_functions.py in log_assign(output_df, input_df, **kwargs)
    250             # If copying is ok, we can check how many values actually changed
    251             for col in changed_cols:
--> 252                 values_changed, values_unchanged = num_values_changed(
    253                     input_df[col], output_df[col]
    254                 )

~/envs/menv/lib/python3.8/site-packages/pandas_log/patched_logs_functions.py in num_values_changed(input_obj, output_obj)
    127         isinstance(input_obj, pd.Series)
    128         and isinstance(output_obj, pd.Series)
--> 129         and input_obj.dtype != output_obj.dtype
    130     ):
    131         # Comparing values for equality across dtypes wouldn't be well-defined so we just say they all changed

TypeError: Cannot interpret 'datetime64[ns, US/Eastern]' as a data type