@@ -8348,7 +8348,7 @@ def abs(self):
83488348
83498349 def describe (self , percentiles = None , include = None , exclude = None ):
83508350 """
8351- Generates descriptive statistics that summarize the central tendency,
8351+ Generate descriptive statistics that summarize the central tendency,
83528352 dispersion and shape of a dataset's distribution, excluding
83538353 ``NaN`` values.
83548354
@@ -8392,7 +8392,18 @@ def describe(self, percentiles=None, include=None, exclude=None):
83928392
83938393 Returns
83948394 -------
8395- summary: Series/DataFrame of summary statistics
8395+ Series or DataFrame
8396+ Summary statistics of the Series or Dataframe provided.
8397+
8398+ See Also
8399+ --------
8400+ DataFrame.count: Count number of non-NA/null observations.
8401+ DataFrame.max: Maximum of the values in the object.
8402+ DataFrame.min: Minimum of the values in the object.
8403+ DataFrame.mean: Mean of the values.
8404+ DataFrame.std: Standard deviation of the obersvations.
8405+ DataFrame.select_dtypes: Subset of a DataFrame including/excluding
8406+ columns based on their dtype.
83968407
83978408 Notes
83988409 -----
@@ -8436,6 +8447,7 @@ def describe(self, percentiles=None, include=None, exclude=None):
84368447 50% 2.0
84378448 75% 2.5
84388449 max 3.0
8450+ dtype: float64
84398451
84408452 Describing a categorical ``Series``.
84418453
@@ -8466,9 +8478,9 @@ def describe(self, percentiles=None, include=None, exclude=None):
84668478 Describing a ``DataFrame``. By default only numeric fields
84678479 are returned.
84688480
8469- >>> df = pd.DataFrame({ 'object ': ['a', 'b', 'c'] ,
8470- ... 'numeric': [1, 2, 3],
8471- ... 'categorical ': pd.Categorical(['d','e','f'])
8481+ >>> df = pd.DataFrame({'categorical ': pd.Categorical(['d','e','f']) ,
8482+ ... 'numeric': [1, 2, 3],
8483+ ... 'object ': ['a', 'b', 'c']
84728484 ... })
84738485 >>> df.describe()
84748486 numeric
@@ -8554,7 +8566,7 @@ def describe(self, percentiles=None, include=None, exclude=None):
85548566 Excluding object columns from a ``DataFrame`` description.
85558567
85568568 >>> df.describe(exclude=[np.object])
8557- categorical numeric
8569+ categorical numeric
85588570 count 3 3.0
85598571 unique 3 NaN
85608572 top f NaN
@@ -8566,15 +8578,6 @@ def describe(self, percentiles=None, include=None, exclude=None):
85668578 50% NaN 2.0
85678579 75% NaN 2.5
85688580 max NaN 3.0
8569-
8570- See Also
8571- --------
8572- DataFrame.count
8573- DataFrame.max
8574- DataFrame.min
8575- DataFrame.mean
8576- DataFrame.std
8577- DataFrame.select_dtypes
85788581 """
85798582 if self .ndim >= 3 :
85808583 msg = "describe is not implemented on Panel objects."
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