I am attempting to go through a time-series dataset and count the number of times each unique category of clothing appears for each day. Every year of my dataset works fine besides 2012. When I run my code I receive a shape broadcasting error and I cannot figure out why 2012 is causing this error but none of my other years are.
test=orders['Category']['2012']
counts = test.groupby(pd.Grouper(freq='D')).value_counts()
ValueError Traceback (most recent call last)
<ipython-input-127-bc2dbf569e47> in <module>()
1 test=orders['Category']['2012']
----> 2 counts = test.groupby(pd.Grouper(freq='D')).value_counts()
c:\users\matthew mclaughlin\miniconda3\envs\cseclass\lib\site-packages\pandas\core\groupby.py in value_counts(self, normalize, sort, ascending, bins, dropna)
3015
3016 # multi-index components
-> 3017 labels = list(map(rep, self.grouper.recons_labels)) + [lab[inc]]
3018 levels = [ping.group_index for ping in self.grouper.groupings] + [lev]
3019 names = self.grouper.names + [self.name]
c:\users\matthew mclaughlin\miniconda3\envs\cseclass\lib\site-packages\numpy\core\fromnumeric.py in repeat(a, repeats, axis)
394 except AttributeError:
395 return _wrapit(a, 'repeat', repeats, axis)
--> 396 return repeat(repeats, axis)
397
398
ValueError: operands could not be broadcast together with shape (366,) (363,)
Order Date
2013-01-01 Outerwear
2013-01-01 Accessories
2013-01-01 First Layer Tops
2013-01-01 First Layer Tops
2013-01-01 Accessories
2013-01-01 First Layer Bottoms
2013-01-01 Kid's Sets
2013-01-01 Outerwear
Order Date Category
2013-01-01 Outerwear 289
First Layer Tops 230
Accessories 190
First Layer Bottoms 155
Footwear 10
Kid's Sets 3
Groupby object has no attribute called .value_counts()
. If you want to value counts use apply
+ stack
i.e
df.groupby(pd.Grouper(freq='D')).apply(lambda x : x.Category.value_counts()).stack()
Output for your test_data with additional dates.
Order Date Category 2013-01-01 Outerwear 3 First Layer Tops 2 Accessories 2 Kid's Sets 1 First Layer Bottoms 1 2013-01-02 Outerwear 3 First Layer Tops 2 Accessories 2 Kid's Sets 1 First Layer Bottoms 1 dtype: int64
If you trying to select categories based on the year then try boolean indexing like df[df.index.year == 2012]