id stringlengths 16 145 | text stringlengths 1 179k | title stringclasses 1
value |
|---|---|---|
pandas_series/pandas_series_193_6.txt | r plot is a plot that presents quantitative data with
rectangular bars with lengths proportional to the values that they represent.
A bar plot shows comparisons among discrete categories. One axis of the plot
shows the specific categories being compared, and the other axis represents a
measured value.
Parameters :
... | |
pandas_series/pandas_series_40_6.txt | ed kurtosis over requested axis.
Kurtosis obtained using Fisherâs definition of kurtosis (kurtosis of normal
== 0.0). Normalized by N-1.
Parameters :
**axis** {index (0)}
Axis for the function to be applied on. For Series this parameter is unused
and defaults to 0.
For DataFrames, specifying ` axi... | |
pandas_series/pandas_series_45_6.txt | ay/Index.
This method takes a time zone (tz) naive Datetime Array/Index object and makes
this time zone aware. It does not move the time to another time zone.
This method can also be used to do the inverse â to create a time zone
unaware object from an aware object. To that end, pass tz=None .
Parameters :
... | |
pandas_series/pandas_series_268_7.txt | __ On this page
* ` Series.apply() `
[ __ Show Source ](../../_sources/reference/api/pandas.Series.apply.rst.txt)
© 2024, pandas via [ NumFOCUS, Inc. ](https://numfocus.org) Hosted by [
OVHcloud ](https://www.ovhcloud.com) .
Created using [ Sphinx ](https://www.sphinx-doc.org/) 7.2.6.
Built with the [ PyData ... | |
pandas_series/pandas.DataFrame.mask.html4_11_0.txt | Entries where cond is True are replaced with corresponding value from other
. If other is callable, it is computed on the Series/DataFrame and should
return scalar or Series/DataFrame. The callable must not change input
Series/DataFrame (though pandas doesnât check it). If not specified, entries
will be filled wit... | |
pandas_series/pandas_series_71_1.txt | html)
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pandas_series/pandas_series_223_7.txt | alse
2 True
3 False
dtype: bool
The ` s5.str.istitle ` method checks for whether all words are in title case
(whether only the first letter of each word is capitalized). Words are assumed
to be as any sequence of non-numeric characters separated by whitespace
characters.
>>> s5.... | |
pandas_series/pandas.DataFrame.mask.html4_25_0.txt | pandas.DataFrame.query
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pandas_series/pandas_series_271_2.txt | vel.html)
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... | |
pandas_series/pandas_series_28_6.txt | n position. It is
useful for quickly verifying data, for example, after sorting or appending
rows.
For negative values of n , this function returns all rows except the first
|n| rows, equivalent to ` df[|n|:] ` .
If n is larger than the number of rows, this function returns all rows.
Parameters :
**n** i... | |
pandas_series/pandas_series_229_5.txt | ndas.Series.cat.rename_categories.html)
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pandas_series/pandas-settingwithcopywarning0_93_0.txt | The argument ` key ` represents the index, which can be an integer , slice
, tuple, list, NumPy array, and so on.
### Indexing in NumPy: Copies and Views | |
pandas_series/pandas_series_171_5.txt | s.Series.cat.rename_categories.html)
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pandas_series/selecting-in-pandas-using-where-and-mask2_19_0.txt | Thanks for subscribing!
>>> np.where(s % 2 != 0, s, 99)
array([99, 1, 99, 3, 99, 5, 99, 7, 99, 9]) | |
pandas_series/pandas_series_330_6.txt |
type of index
Examples
For Series:
>>> s = pd.Series([None, 3, 4])
>>> s.first_valid_index()
1
>>> s.last_valid_index()
2
>>> s = pd.Series([None, None])
>>> print(s.first_valid_index())
None
>>> print(s.last_valid_index())
None
If al... | |
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pandas_series/pandas_series_300_6.txt | This method is available directly on TimedeltaArray, TimedeltaIndex and on
Series containing timedelta values under the ` .dt ` namespace.
Returns :
ndarray, Index or Series
When the calling object is a TimedeltaArray, the return type is ndarray. When
the calling object is a TimedeltaIndex, the return ... | |
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pandas_series/pandas-settingwithcopywarning0_153_0.txt | ### Impact of Data Types on Views, Copies, and the ` SettingWithCopyWarning `
In pandas, the difference between creating views and creating copies also
depends on the data types used. When deciding if it’s going to return a view
or copy, pandas handles DataFrames that have a single data type differently
from ones wit... | |
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pandas_series/pandas_series_47_6.txt | imum over a DataFrame or Series axis.
Returns a DataFrame or Series of the same size containing the cumulative
minimum.
Parameters :
**axis** {0 or âindexâ, 1 or âcolumnsâ}, default 0
The index or the name of the axis. 0 is equivalent to None or âindexâ. For
Series this parameter is unused... | |
pandas_series/pandas_series_133_4.txt | ndas.Series.str.capitalize ](pandas.Series.str.capitalize.html)
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pandas_series/dataframe-indexing.html6_22_0.txt |
>>> ddf.partitions[::2]
Dask DataFrame Structure:
name id x y
npartitions=3
2021-01-01 object int64 float64 float64
2021-01-03 ... ... ... ...
2021-01-05 ... ... ... ...
2021-01-06 ... .... | |
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pandas_series/pandas-settingwithcopywarning0_77_0.txt | Python
>>> arr[1] = 64
>>> arr
array([ 1, 64, 4, 8, 16, 32])
>>> view_of_arr
array([ 1, 64, 4, 8, 16, 32])
>>> copy_of_arr
array([ 1, 2, 4, 8, 16, 32])
| |
pandas_series/pandas-settingwithcopywarning0_102_0.txt | You can also index NumPy arrays with mask arrays or lists. Masks are Boolean
arrays or lists of the same shape as the original. You’ll get a copy of the
original array that contains only the elements that correspond to the ` True `
values of the mask:
Python | |
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pandas_series/pandas-settingwithcopywarning0_42_0.txt | Copied!
This approach enables you to provide two arguments, ` mask ` and ` "z" ` , to
the single method that assigns the values to the DataFrame. | |
pandas_series/pandas-settingwithcopywarning0_170_0.txt | Python
>>> df.loc[["a", "b"], ("powers", "x")]
a 1
b 2
Name: (powers, x), dtype: int64
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pandas_series/pandas-settingwithcopywarning0_190_0.txt | In this article, you learned what views and copies are in NumPy and pandas and
what the differences are in their behavior. You also saw what a `
SettingWithCopyWarning ` is and how to avoid the subtle errors it points to.
In particular, you’ve learned the following: | |
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pandas_series/pandas.DataFrame.mask.html4_12_0.txt |
Whether to perform the operation in place on the data. | |
pandas_series/pandas_series_127_3.txt | ml)
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pandas_series/pandas_series_236_6.txt | DataFrame.
For each subject string in the Series, extract groups from all matches of
regular expression pat. When each subject string in the Series has exactly one
match, extractall(pat).xs(0, level=âmatchâ) is the same as extract(pat).
Parameters :
**pat** str
Regular expression pattern with captu... | |
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pandas_series/pandas_series_213_1.txt | html)
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pandas_series/pandas_series_81_5.txt | pandas.Series.cat.rename_categories.html)
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pandas_series/pandas_series_54_6.txt | ts** int or sequence of int
Same value for all (int) or different value per (sequence).
Returns :
Series or pandas.Index
Series or Index of repeated string objects specified by input parameter
repeats.
Examples
>>> s = pd.Series(['a', 'b', 'c'])
>>> s
0 a
1 b
... | |
pandas_series/pandas-settingwithcopywarning0_131_0.txt |
>>> df = pd.DataFrame(data=data, index=index)
>>> df[["x", "y"]]
x y
a 1 1
b 2 3
c 4 9
d 8 27
e 16 81
>>> df[["x", "y"]].to_numpy().base
array([[ 1, 2, 4, 8, 16],
[ 1, 3, 9, 27, 81]])
>>> df[["x", "y"]].to_numpy(... | |
pandas_series/pandas_series_259_3.txt | ml)
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pandas_series/pandas-settingwithcopywarning0_104_0.txt | The list ` mask ` has ` True ` values at the second and fourth positions. This
is why the array ` d ` contains only the elements from the second and fourth
positions of ` arr ` . As in the case of ` c ` , ` d ` is a copy, its ` .base
` is ` None ` , and it has its own data:
The elements of ` arr ` in the green rectang... | |
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pandas_series/pandas-settingwithcopywarning0_167_0.txt | Copied!
That’s one way to get and set columns in the case of multilevel column
indices. You can also use accessors with multi-indexed DataFrames to get or
modify the data: | |
pandas_series/pandas-settingwithcopywarning0_123_0.txt | You changed the value ` 2 ` in ` arr ` to ` 100 ` and altered the
corresponding elements from the views ` a ` and ` b ` . The copies ` c ` and `
d ` can’t be modified this way.
To learn more about indexing NumPy arrays, you can check out the official
quickstart tutorial and indexing tutorial . | |
pandas_series/pandas_series_225_4.txt | ndas.Series.str.capitalize.html)
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