@@ -320,7 +320,7 @@ class DataFrame(NDFrame):
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DataFrame.from_records : Constructor from tuples, also record arrays.
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DataFrame.from_dict : From dicts of Series, arrays, or dicts.
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DataFrame.from_items : From sequence of (key, value) pairs
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- pandas. read_csv, pandas.read_table, pandas.read_clipboard.
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+ read_csv, pandas.read_table, pandas.read_clipboard.
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Examples
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--------
@@ -735,7 +735,7 @@ def style(self):
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See Also
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--------
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- pandas. io.formats.style.Styler
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+ io.formats.style.Styler
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"""
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from pandas .io .formats .style import Styler
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return Styler (self )
@@ -1417,7 +1417,7 @@ def to_gbq(self, destination_table, project_id=None, chunksize=None,
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See Also
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--------
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pandas_gbq.to_gbq : This function in the pandas-gbq library.
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- pandas. read_gbq : Read a DataFrame from Google BigQuery.
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+ read_gbq : Read a DataFrame from Google BigQuery.
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"""
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from pandas .io import gbq
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return gbq .to_gbq (
@@ -1843,14 +1843,14 @@ def from_csv(cls, path, header=0, sep=',', index_col=0, parse_dates=True,
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Read CSV file.
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.. deprecated:: 0.21.0
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- Use :func:`pandas. read_csv` instead.
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+ Use :func:`read_csv` instead.
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- It is preferable to use the more powerful :func:`pandas. read_csv`
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+ It is preferable to use the more powerful :func:`read_csv`
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for most general purposes, but ``from_csv`` makes for an easy
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roundtrip to and from a file (the exact counterpart of
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``to_csv``), especially with a DataFrame of time series data.
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- This method only differs from the preferred :func:`pandas. read_csv`
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+ This method only differs from the preferred :func:`read_csv`
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in some defaults:
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- `index_col` is ``0`` instead of ``None`` (take first column as index
@@ -1887,7 +1887,7 @@ def from_csv(cls, path, header=0, sep=',', index_col=0, parse_dates=True,
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See Also
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--------
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- pandas. read_csv
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+ read_csv
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"""
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warnings .warn ("from_csv is deprecated. Please use read_csv(...) "
@@ -2504,7 +2504,7 @@ def memory_usage(self, index=True, deep=False):
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numpy.ndarray.nbytes : Total bytes consumed by the elements of an
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ndarray.
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Series.memory_usage : Bytes consumed by a Series.
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- pandas. Categorical : Memory-efficient array for string values with
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+ Categorical : Memory-efficient array for string values with
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many repeated values.
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DataFrame.info : Concise summary of a DataFrame.
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@@ -2987,7 +2987,7 @@ def query(self, expr, inplace=False, **kwargs):
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Whether the query should modify the data in place or return
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a modified copy.
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**kwargs
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- See the documentation for :func:`pandas. eval` for complete details
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+ See the documentation for :func:`eval` for complete details
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on the keyword arguments accepted by :meth:`DataFrame.query`.
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.. versionadded:: 0.18.0
@@ -3011,7 +3011,7 @@ def query(self, expr, inplace=False, **kwargs):
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multidimensional key (e.g., a DataFrame) then the result will be passed
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to :meth:`DataFrame.__getitem__`.
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- This method uses the top-level :func:`pandas. eval` function to
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+ This method uses the top-level :func:`eval` function to
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evaluate the passed query.
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The :meth:`~pandas.DataFrame.query` method uses a slightly
@@ -3098,7 +3098,7 @@ def eval(self, expr, inplace=False, **kwargs):
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.. versionadded:: 0.18.0.
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kwargs : dict
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- See the documentation for :func:`~pandas. eval` for complete details
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+ See the documentation for :func:`eval` for complete details
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on the keyword arguments accepted by
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:meth:`~pandas.DataFrame.query`.
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@@ -3113,12 +3113,12 @@ def eval(self, expr, inplace=False, **kwargs):
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of a frame.
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DataFrame.assign : Can evaluate an expression or function to create new
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values for a column.
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- pandas. eval : Evaluate a Python expression as a string using various
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+ eval : Evaluate a Python expression as a string using various
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backends.
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Notes
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-----
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- For more details see the API documentation for :func:`~pandas. eval`.
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+ For more details see the API documentation for :func:`~eval`.
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For detailed examples see :ref:`enhancing performance with eval
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<enhancingperf.eval>`.
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@@ -3957,7 +3957,7 @@ def rename(self, *args, **kwargs):
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See Also
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--------
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- pandas. DataFrame.rename_axis
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+ DataFrame.rename_axis
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Examples
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--------
@@ -6203,11 +6203,11 @@ def _gotitem(self,
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--------
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DataFrame.apply : Perform any type of operations.
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DataFrame.transform : Perform transformation type operations.
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- pandas. core.groupby.GroupBy : Perform operations over groups.
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- pandas. core.resample.Resampler : Perform operations over resampled bins.
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- pandas. core.window.Rolling : Perform operations over rolling window.
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- pandas. core.window.Expanding : Perform operations over expanding window.
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- pandas. core.window.EWM : Perform operation over exponential weighted
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+ core.groupby.GroupBy : Perform operations over groups.
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+ core.resample.Resampler : Perform operations over resampled bins.
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+ core.window.Rolling : Perform operations over rolling window.
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+ core.window.Expanding : Perform operations over expanding window.
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+ core.window.EWM : Perform operation over exponential weighted
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window.
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""" )
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@@ -6559,7 +6559,7 @@ def append(self, other, ignore_index=False,
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See Also
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--------
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- pandas. concat : General function to concatenate DataFrame, Series
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+ concat : General function to concatenate DataFrame, Series
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or Panel objects.
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Notes
@@ -7069,10 +7069,10 @@ def cov(self, min_periods=None):
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See Also
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--------
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- pandas. Series.cov : Compute covariance with another Series.
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- pandas. core.window.EWM.cov: Exponential weighted sample covariance.
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- pandas. core.window.Expanding.cov : Expanding sample covariance.
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- pandas. core.window.Rolling.cov : Rolling sample covariance.
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+ Series.cov : Compute covariance with another Series.
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+ core.window.EWM.cov: Exponential weighted sample covariance.
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+ core.window.Expanding.cov : Expanding sample covariance.
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+ core.window.Rolling.cov : Rolling sample covariance.
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Notes
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-----
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