doc_content stringlengths 1 386k | doc_id stringlengths 5 188 |
|---|---|
pandas.Index.value_counts Index.value_counts(normalize=False, sort=True, ascending=False, bins=None, dropna=True)[source]
Return a Series containing counts of unique values. The resulting object will be in descending order so that the first element is the most frequently-occurring element. Excludes NA values by def... | pandas.reference.api.pandas.index.value_counts |
pandas.Index.values propertyIndex.values
Return an array representing the data in the Index. Warning We recommend using Index.array or Index.to_numpy(), depending on whether you need a reference to the underlying data or a NumPy array. Returns
array: numpy.ndarray or ExtensionArray
See also Index.array
R... | pandas.reference.api.pandas.index.values |
pandas.Index.view Index.view(cls=None)[source] | pandas.reference.api.pandas.index.view |
pandas.Index.where finalIndex.where(cond, other=None)[source]
Replace values where the condition is False. The replacement is taken from other. Parameters
cond:bool array-like with the same length as self
Condition to select the values on.
other:scalar, or array-like, default None
Replacement if the condi... | pandas.reference.api.pandas.index.where |
pandas.IndexSlice pandas.IndexSlice=<pandas.core.indexing._IndexSlice object>
Create an object to more easily perform multi-index slicing. See also MultiIndex.remove_unused_levels
New MultiIndex with no unused levels. Notes See Defined Levels for further info on slicing a MultiIndex. Examples
>>> midx = pd.M... | pandas.reference.api.pandas.indexslice |
pandas.infer_freq pandas.infer_freq(index, warn=True)[source]
Infer the most likely frequency given the input index. If the frequency is uncertain, a warning will be printed. Parameters
index:DatetimeIndex or TimedeltaIndex
If passed a Series will use the values of the series (NOT THE INDEX).
warn:bool, def... | pandas.reference.api.pandas.infer_freq |
pandas.Int16Dtype classpandas.Int16Dtype[source]
An ExtensionDtype for int16 integer data. Changed in version 1.0.0: Now uses pandas.NA as its missing value, rather than numpy.nan. Attributes
None Methods
None | pandas.reference.api.pandas.int16dtype |
pandas.Int32Dtype classpandas.Int32Dtype[source]
An ExtensionDtype for int32 integer data. Changed in version 1.0.0: Now uses pandas.NA as its missing value, rather than numpy.nan. Attributes
None Methods
None | pandas.reference.api.pandas.int32dtype |
pandas.Int64Dtype classpandas.Int64Dtype[source]
An ExtensionDtype for int64 integer data. Changed in version 1.0.0: Now uses pandas.NA as its missing value, rather than numpy.nan. Attributes
None Methods
None | pandas.reference.api.pandas.int64dtype |
pandas.Int64Index classpandas.Int64Index(data=None, dtype=None, copy=False, name=None)[source]
Immutable sequence used for indexing and alignment. The basic object storing axis labels for all pandas objects. Int64Index is a special case of Index with purely integer labels. . Deprecated since version 1.4.0: In pand... | pandas.reference.api.pandas.int64index |
pandas.Int8Dtype classpandas.Int8Dtype[source]
An ExtensionDtype for int8 integer data. Changed in version 1.0.0: Now uses pandas.NA as its missing value, rather than numpy.nan. Attributes
None Methods
None | pandas.reference.api.pandas.int8dtype |
pandas.Interval classpandas.Interval
Immutable object implementing an Interval, a bounded slice-like interval. Parameters
left:orderable scalar
Left bound for the interval.
right:orderable scalar
Right bound for the interval.
closed:{‘right’, ‘left’, ‘both’, ‘neither’}, default ‘right’
Whether the int... | pandas.reference.api.pandas.interval |
pandas.Interval.closed Interval.closed
Whether the interval is closed on the left-side, right-side, both or neither. | pandas.reference.api.pandas.interval.closed |
pandas.Interval.closed_left Interval.closed_left
Check if the interval is closed on the left side. For the meaning of closed and open see Interval. Returns
bool
True if the Interval is closed on the left-side. | pandas.reference.api.pandas.interval.closed_left |
pandas.Interval.closed_right Interval.closed_right
Check if the interval is closed on the right side. For the meaning of closed and open see Interval. Returns
bool
True if the Interval is closed on the left-side. | pandas.reference.api.pandas.interval.closed_right |
pandas.Interval.is_empty Interval.is_empty
Indicates if an interval is empty, meaning it contains no points. New in version 0.25.0. Returns
bool or ndarray
A boolean indicating if a scalar Interval is empty, or a boolean ndarray positionally indicating if an Interval in an IntervalArray or IntervalIndex is em... | pandas.reference.api.pandas.interval.is_empty |
pandas.Interval.left Interval.left
Left bound for the interval. | pandas.reference.api.pandas.interval.left |
pandas.Interval.length Interval.length
Return the length of the Interval. | pandas.reference.api.pandas.interval.length |
pandas.Interval.mid Interval.mid
Return the midpoint of the Interval. | pandas.reference.api.pandas.interval.mid |
pandas.Interval.open_left Interval.open_left
Check if the interval is open on the left side. For the meaning of closed and open see Interval. Returns
bool
True if the Interval is closed on the left-side. | pandas.reference.api.pandas.interval.open_left |
pandas.Interval.open_right Interval.open_right
Check if the interval is open on the right side. For the meaning of closed and open see Interval. Returns
bool
True if the Interval is closed on the left-side. | pandas.reference.api.pandas.interval.open_right |
pandas.Interval.overlaps Interval.overlaps()
Check whether two Interval objects overlap. Two intervals overlap if they share a common point, including closed endpoints. Intervals that only have an open endpoint in common do not overlap. Parameters
other:Interval
Interval to check against for an overlap. Re... | pandas.reference.api.pandas.interval.overlaps |
pandas.Interval.right Interval.right
Right bound for the interval. | pandas.reference.api.pandas.interval.right |
pandas.interval_range pandas.interval_range(start=None, end=None, periods=None, freq=None, name=None, closed='right')[source]
Return a fixed frequency IntervalIndex. Parameters
start:numeric or datetime-like, default None
Left bound for generating intervals.
end:numeric or datetime-like, default None
Righ... | pandas.reference.api.pandas.interval_range |
pandas.IntervalDtype classpandas.IntervalDtype(subtype=None, closed=None)[source]
An ExtensionDtype for Interval data. This is not an actual numpy dtype, but a duck type. Parameters
subtype:str, np.dtype
The dtype of the Interval bounds. Examples
>>> pd.IntervalDtype(subtype='int64', closed='both')
inter... | pandas.reference.api.pandas.intervaldtype |
pandas.IntervalDtype.subtype propertyIntervalDtype.subtype
The dtype of the Interval bounds. | pandas.reference.api.pandas.intervaldtype.subtype |
pandas.IntervalIndex classpandas.IntervalIndex(data, closed=None, dtype=None, copy=False, name=None, verify_integrity=True)[source]
Immutable index of intervals that are closed on the same side. New in version 0.20.0. Parameters
data:array-like (1-dimensional)
Array-like containing Interval objects from whi... | pandas.reference.api.pandas.intervalindex |
pandas.IntervalIndex.closed IntervalIndex.closed
Whether the intervals are closed on the left-side, right-side, both or neither. | pandas.reference.api.pandas.intervalindex.closed |
pandas.IntervalIndex.contains IntervalIndex.contains(*args, **kwargs)[source]
Check elementwise if the Intervals contain the value. Return a boolean mask whether the value is contained in the Intervals of the IntervalArray. New in version 0.25.0. Parameters
other:scalar
The value to check whether it is cont... | pandas.reference.api.pandas.intervalindex.contains |
pandas.IntervalIndex.from_arrays classmethodIntervalIndex.from_arrays(left, right, closed='right', name=None, copy=False, dtype=None)[source]
Construct from two arrays defining the left and right bounds. Parameters
left:array-like (1-dimensional)
Left bounds for each interval.
right:array-like (1-dimensiona... | pandas.reference.api.pandas.intervalindex.from_arrays |
pandas.IntervalIndex.from_breaks classmethodIntervalIndex.from_breaks(breaks, closed='right', name=None, copy=False, dtype=None)[source]
Construct an IntervalIndex from an array of splits. Parameters
breaks:array-like (1-dimensional)
Left and right bounds for each interval.
closed:{‘left’, ‘right’, ‘both’, ... | pandas.reference.api.pandas.intervalindex.from_breaks |
pandas.IntervalIndex.from_tuples classmethodIntervalIndex.from_tuples(data, closed='right', name=None, copy=False, dtype=None)[source]
Construct an IntervalIndex from an array-like of tuples. Parameters
data:array-like (1-dimensional)
Array of tuples.
closed:{‘left’, ‘right’, ‘both’, ‘neither’}, default ‘ri... | pandas.reference.api.pandas.intervalindex.from_tuples |
pandas.IntervalIndex.get_indexer IntervalIndex.get_indexer(target, method=None, limit=None, tolerance=None)[source]
Compute indexer and mask for new index given the current index. The indexer should be then used as an input to ndarray.take to align the current data to the new index. Parameters
target:Index
me... | pandas.reference.api.pandas.intervalindex.get_indexer |
pandas.IntervalIndex.get_loc IntervalIndex.get_loc(key, method=None, tolerance=None)[source]
Get integer location, slice or boolean mask for requested label. Parameters
key:label
method:{None}, optional
default: matches where the label is within an interval only. Returns
int if unique index, slice if... | pandas.reference.api.pandas.intervalindex.get_loc |
pandas.IntervalIndex.is_empty propertyIntervalIndex.is_empty
Indicates if an interval is empty, meaning it contains no points. New in version 0.25.0. Returns
bool or ndarray
A boolean indicating if a scalar Interval is empty, or a boolean ndarray positionally indicating if an Interval in an IntervalArray or I... | pandas.reference.api.pandas.intervalindex.is_empty |
pandas.IntervalIndex.is_non_overlapping_monotonic IntervalIndex.is_non_overlapping_monotonic
Return True if the IntervalArray is non-overlapping (no Intervals share points) and is either monotonic increasing or monotonic decreasing, else False. | pandas.reference.api.pandas.intervalindex.is_non_overlapping_monotonic |
pandas.IntervalIndex.is_overlapping propertyIntervalIndex.is_overlapping
Return True if the IntervalIndex has overlapping intervals, else False. Two intervals overlap if they share a common point, including closed endpoints. Intervals that only have an open endpoint in common do not overlap. Returns
bool
Boolea... | pandas.reference.api.pandas.intervalindex.is_overlapping |
pandas.IntervalIndex.left IntervalIndex.left | pandas.reference.api.pandas.intervalindex.left |
pandas.IntervalIndex.length propertyIntervalIndex.length | pandas.reference.api.pandas.intervalindex.length |
pandas.IntervalIndex.mid IntervalIndex.mid | pandas.reference.api.pandas.intervalindex.mid |
pandas.IntervalIndex.overlaps IntervalIndex.overlaps(*args, **kwargs)[source]
Check elementwise if an Interval overlaps the values in the IntervalArray. Two intervals overlap if they share a common point, including closed endpoints. Intervals that only have an open endpoint in common do not overlap. Parameters
... | pandas.reference.api.pandas.intervalindex.overlaps |
pandas.IntervalIndex.right IntervalIndex.right | pandas.reference.api.pandas.intervalindex.right |
pandas.IntervalIndex.set_closed IntervalIndex.set_closed(*args, **kwargs)[source]
Return an IntervalArray identical to the current one, but closed on the specified side. Parameters
closed:{‘left’, ‘right’, ‘both’, ‘neither’}
Whether the intervals are closed on the left-side, right-side, both or neither. Re... | pandas.reference.api.pandas.intervalindex.set_closed |
pandas.IntervalIndex.to_tuples IntervalIndex.to_tuples(*args, **kwargs)[source]
Return an ndarray of tuples of the form (left, right). Parameters
na_tuple:bool, default True
Returns NA as a tuple if True, (nan, nan), or just as the NA value itself if False, nan. Returns
tuples: ndarray | pandas.reference.api.pandas.intervalindex.to_tuples |
pandas.IntervalIndex.values propertyIntervalIndex.values
Return an array representing the data in the Index. Warning We recommend using Index.array or Index.to_numpy(), depending on whether you need a reference to the underlying data or a NumPy array. Returns
array: numpy.ndarray or ExtensionArray
See also... | pandas.reference.api.pandas.intervalindex.values |
pandas.io.formats.style.Styler classpandas.io.formats.style.Styler(data, precision=None, table_styles=None, uuid=None, caption=None, table_attributes=None, cell_ids=True, na_rep=None, uuid_len=5, decimal=None, thousands=None, escape=None, formatter=None)[source]
Helps style a DataFrame or Series according to the da... | pandas.reference.api.pandas.io.formats.style.styler |
pandas.io.formats.style.Styler.apply Styler.apply(func, axis=0, subset=None, **kwargs)[source]
Apply a CSS-styling function column-wise, row-wise, or table-wise. Updates the HTML representation with the result. Parameters
func:function
func should take a Series if axis in [0,1] and return a list-like object o... | pandas.reference.api.pandas.io.formats.style.styler.apply |
pandas.io.formats.style.Styler.apply_index Styler.apply_index(func, axis=0, level=None, **kwargs)[source]
Apply a CSS-styling function to the index or column headers, level-wise. Updates the HTML representation with the result. New in version 1.4.0. Parameters
func:function
func should take a Series and ret... | pandas.reference.api.pandas.io.formats.style.styler.apply_index |
pandas.io.formats.style.Styler.applymap Styler.applymap(func, subset=None, **kwargs)[source]
Apply a CSS-styling function elementwise. Updates the HTML representation with the result. Parameters
func:function
func should take a scalar and return a string.
subset:label, array-like, IndexSlice, optional
A v... | pandas.reference.api.pandas.io.formats.style.styler.applymap |
pandas.io.formats.style.Styler.applymap_index Styler.applymap_index(func, axis=0, level=None, **kwargs)[source]
Apply a CSS-styling function to the index or column headers, elementwise. Updates the HTML representation with the result. New in version 1.4.0. Parameters
func:function
func should take a scalar ... | pandas.reference.api.pandas.io.formats.style.styler.applymap_index |
pandas.io.formats.style.Styler.background_gradient Styler.background_gradient(cmap='PuBu', low=0, high=0, axis=0, subset=None, text_color_threshold=0.408, vmin=None, vmax=None, gmap=None)[source]
Color the background in a gradient style. The background color is determined according to the data in each column, row o... | pandas.reference.api.pandas.io.formats.style.styler.background_gradient |
pandas.io.formats.style.Styler.bar Styler.bar(subset=None, axis=0, *, color=None, cmap=None, width=100, height=100, align='mid', vmin=None, vmax=None, props='width: 10em;')[source]
Draw bar chart in the cell backgrounds. Changed in version 1.4.0. Parameters
subset:label, array-like, IndexSlice, optional
A v... | pandas.reference.api.pandas.io.formats.style.styler.bar |
pandas.io.formats.style.Styler.clear Styler.clear()[source]
Reset the Styler, removing any previously applied styles. Returns None. | pandas.reference.api.pandas.io.formats.style.styler.clear |
pandas.io.formats.style.Styler.env Styler.env=<jinja2.environment.Environment object> | pandas.reference.api.pandas.io.formats.style.styler.env |
pandas.io.formats.style.Styler.export Styler.export()[source]
Export the styles applied to the current Styler. Can be applied to a second Styler with Styler.use. Returns
styles:dict
See also Styler.use
Set the styles on the current Styler. Styler.copy
Create a copy of the current Styler. Notes This ... | pandas.reference.api.pandas.io.formats.style.styler.export |
pandas.io.formats.style.Styler.format Styler.format(formatter=None, subset=None, na_rep=None, precision=None, decimal='.', thousands=None, escape=None, hyperlinks=None)[source]
Format the text display value of cells. Parameters
formatter:str, callable, dict or None
Object to define how values are displayed. S... | pandas.reference.api.pandas.io.formats.style.styler.format |
pandas.io.formats.style.Styler.format_index Styler.format_index(formatter=None, axis=0, level=None, na_rep=None, precision=None, decimal='.', thousands=None, escape=None, hyperlinks=None)[source]
Format the text display value of index labels or column headers. New in version 1.4.0. Parameters
formatter:str, c... | pandas.reference.api.pandas.io.formats.style.styler.format_index |
pandas.io.formats.style.Styler.from_custom_template classmethodStyler.from_custom_template(searchpath, html_table=None, html_style=None)[source]
Factory function for creating a subclass of Styler. Uses custom templates and Jinja environment. Changed in version 1.3.0. Parameters
searchpath:str or list
Path o... | pandas.reference.api.pandas.io.formats.style.styler.from_custom_template |
pandas.io.formats.style.Styler.hide Styler.hide(subset=None, axis=0, level=None, names=False)[source]
Hide the entire index / column headers, or specific rows / columns from display. New in version 1.4.0. Parameters
subset:label, array-like, IndexSlice, optional
A valid 1d input or single key along the axis... | pandas.reference.api.pandas.io.formats.style.styler.hide |
pandas.io.formats.style.Styler.hide_columns Styler.hide_columns(subset=None, level=None, names=False)[source]
Hide the column headers or specific keys in the columns from rendering. This method has dual functionality:
if subset is None then the entire column headers row, or specific levels, will be hidden whilst... | pandas.reference.api.pandas.io.formats.style.styler.hide_columns |
pandas.io.formats.style.Styler.hide_index Styler.hide_index(subset=None, level=None, names=False)[source]
Hide the entire index, or specific keys in the index from rendering. This method has dual functionality:
if subset is None then the entire index, or specified levels, will be hidden whilst displaying all dat... | pandas.reference.api.pandas.io.formats.style.styler.hide_index |
pandas.io.formats.style.Styler.highlight_between Styler.highlight_between(subset=None, color='yellow', axis=0, left=None, right=None, inclusive='both', props=None)[source]
Highlight a defined range with a style. New in version 1.3.0. Parameters
subset:label, array-like, IndexSlice, optional
A valid 2d input... | pandas.reference.api.pandas.io.formats.style.styler.highlight_between |
pandas.io.formats.style.Styler.highlight_max Styler.highlight_max(subset=None, color='yellow', axis=0, props=None)[source]
Highlight the maximum with a style. Parameters
subset:label, array-like, IndexSlice, optional
A valid 2d input to DataFrame.loc[<subset>], or, in the case of a 1d input or single key, to ... | pandas.reference.api.pandas.io.formats.style.styler.highlight_max |
pandas.io.formats.style.Styler.highlight_min Styler.highlight_min(subset=None, color='yellow', axis=0, props=None)[source]
Highlight the minimum with a style. Parameters
subset:label, array-like, IndexSlice, optional
A valid 2d input to DataFrame.loc[<subset>], or, in the case of a 1d input or single key, to ... | pandas.reference.api.pandas.io.formats.style.styler.highlight_min |
pandas.io.formats.style.Styler.highlight_null Styler.highlight_null(null_color='red', subset=None, props=None)[source]
Highlight missing values with a style. Parameters
null_color:str, default ‘red’
subset:label, array-like, IndexSlice, optional
A valid 2d input to DataFrame.loc[<subset>], or, in the case o... | pandas.reference.api.pandas.io.formats.style.styler.highlight_null |
pandas.io.formats.style.Styler.highlight_quantile Styler.highlight_quantile(subset=None, color='yellow', axis=0, q_left=0.0, q_right=1.0, interpolation='linear', inclusive='both', props=None)[source]
Highlight values defined by a quantile with a style. New in version 1.3.0. Parameters
subset:label, array-like... | pandas.reference.api.pandas.io.formats.style.styler.highlight_quantile |
pandas.io.formats.style.Styler.loader Styler.loader=<jinja2.loaders.PackageLoader object> | pandas.reference.api.pandas.io.formats.style.styler.loader |
pandas.io.formats.style.Styler.pipe Styler.pipe(func, *args, **kwargs)[source]
Apply func(self, *args, **kwargs), and return the result. Parameters
func:function
Function to apply to the Styler. Alternatively, a (callable, keyword) tuple where keyword is a string indicating the keyword of callable that expect... | pandas.reference.api.pandas.io.formats.style.styler.pipe |
pandas.io.formats.style.Styler.render Styler.render(sparse_index=None, sparse_columns=None, **kwargs)[source]
Render the Styler including all applied styles to HTML. Deprecated since version 1.4.0. Parameters
sparse_index:bool, optional
Whether to sparsify the display of a hierarchical index. Setting to Fal... | pandas.reference.api.pandas.io.formats.style.styler.render |
pandas.io.formats.style.Styler.set_caption Styler.set_caption(caption)[source]
Set the text added to a <caption> HTML element. Parameters
caption:str, tuple
For HTML output either the string input is used or the first element of the tuple. For LaTeX the string input provides a caption and the additional tuple... | pandas.reference.api.pandas.io.formats.style.styler.set_caption |
pandas.io.formats.style.Styler.set_na_rep Styler.set_na_rep(na_rep)[source]
Set the missing data representation on a Styler. New in version 1.0.0. Deprecated since version 1.3.0. Parameters
na_rep:str
Returns
self:Styler
Notes This method is deprecated. See Styler.format() | pandas.reference.api.pandas.io.formats.style.styler.set_na_rep |
pandas.io.formats.style.Styler.set_precision Styler.set_precision(precision)[source]
Set the precision used to display values. Deprecated since version 1.3.0. Parameters
precision:int
Returns
self:Styler
Notes This method is deprecated see Styler.format. | pandas.reference.api.pandas.io.formats.style.styler.set_precision |
pandas.io.formats.style.Styler.set_properties Styler.set_properties(subset=None, **kwargs)[source]
Set defined CSS-properties to each <td> HTML element within the given subset. Parameters
subset:label, array-like, IndexSlice, optional
A valid 2d input to DataFrame.loc[<subset>], or, in the case of a 1d input ... | pandas.reference.api.pandas.io.formats.style.styler.set_properties |
pandas.io.formats.style.Styler.set_sticky Styler.set_sticky(axis=0, pixel_size=None, levels=None)[source]
Add CSS to permanently display the index or column headers in a scrolling frame. Parameters
axis:{0 or ‘index’, 1 or ‘columns’}, default 0
Whether to make the index or column headers sticky.
pixel_size:... | pandas.reference.api.pandas.io.formats.style.styler.set_sticky |
pandas.io.formats.style.Styler.set_table_attributes Styler.set_table_attributes(attributes)[source]
Set the table attributes added to the <table> HTML element. These are items in addition to automatic (by default) id attribute. Parameters
attributes:str
Returns
self:Styler
See also Styler.set_table_... | pandas.reference.api.pandas.io.formats.style.styler.set_table_attributes |
pandas.io.formats.style.Styler.set_table_styles Styler.set_table_styles(table_styles=None, axis=0, overwrite=True, css_class_names=None)[source]
Set the table styles included within the <style> HTML element. This function can be used to style the entire table, columns, rows or specific HTML selectors. Parameters
... | pandas.reference.api.pandas.io.formats.style.styler.set_table_styles |
pandas.io.formats.style.Styler.set_td_classes Styler.set_td_classes(classes)[source]
Set the DataFrame of strings added to the class attribute of <td> HTML elements. Parameters
classes:DataFrame
DataFrame containing strings that will be translated to CSS classes, mapped by identical column and index key value... | pandas.reference.api.pandas.io.formats.style.styler.set_td_classes |
pandas.io.formats.style.Styler.set_tooltips Styler.set_tooltips(ttips, props=None, css_class=None)[source]
Set the DataFrame of strings on Styler generating :hover tooltips. These string based tooltips are only applicable to <td> HTML elements, and cannot be used for column or index headers. New in version 1.3.0. ... | pandas.reference.api.pandas.io.formats.style.styler.set_tooltips |
pandas.io.formats.style.Styler.set_uuid Styler.set_uuid(uuid)[source]
Set the uuid applied to id attributes of HTML elements. Parameters
uuid:str
Returns
self:Styler
Notes Almost all HTML elements within the table, and including the <table> element are assigned id attributes. The format is T_uuid_<ext... | pandas.reference.api.pandas.io.formats.style.styler.set_uuid |
pandas.io.formats.style.Styler.template_html Styler.template_html=<Template 'html.tpl'> | pandas.reference.api.pandas.io.formats.style.styler.template_html |
pandas.io.formats.style.Styler.template_html_style Styler.template_html_style=<Template 'html_style.tpl'> | pandas.reference.api.pandas.io.formats.style.styler.template_html_style |
pandas.io.formats.style.Styler.template_html_table Styler.template_html_table=<Template 'html_table.tpl'> | pandas.reference.api.pandas.io.formats.style.styler.template_html_table |
pandas.io.formats.style.Styler.template_latex Styler.template_latex=<Template 'latex.tpl'> | pandas.reference.api.pandas.io.formats.style.styler.template_latex |
pandas.io.formats.style.Styler.text_gradient Styler.text_gradient(cmap='PuBu', low=0, high=0, axis=0, subset=None, vmin=None, vmax=None, gmap=None)[source]
Color the text in a gradient style. The text color is determined according to the data in each column, row or frame, or by a given gradient map. Requires matplo... | pandas.reference.api.pandas.io.formats.style.styler.text_gradient |
pandas.io.formats.style.Styler.to_excel Styler.to_excel(excel_writer, sheet_name='Sheet1', na_rep='', float_format=None, columns=None, header=True, index=True, index_label=None, startrow=0, startcol=0, engine=None, merge_cells=True, encoding=None, inf_rep='inf', verbose=True, freeze_panes=None)[source]
Write Styler... | pandas.reference.api.pandas.io.formats.style.styler.to_excel |
pandas.io.formats.style.Styler.to_html Styler.to_html(buf=None, *, table_uuid=None, table_attributes=None, sparse_index=None, sparse_columns=None, bold_headers=False, caption=None, max_rows=None, max_columns=None, encoding=None, doctype_html=False, exclude_styles=False, **kwargs)[source]
Write Styler to a file, buf... | pandas.reference.api.pandas.io.formats.style.styler.to_html |
pandas.io.formats.style.Styler.to_latex Styler.to_latex(buf=None, *, column_format=None, position=None, position_float=None, hrules=None, clines=None, label=None, caption=None, sparse_index=None, sparse_columns=None, multirow_align=None, multicol_align=None, siunitx=False, environment=None, encoding=None, convert_css... | pandas.reference.api.pandas.io.formats.style.styler.to_latex |
pandas.io.formats.style.Styler.use Styler.use(styles)[source]
Set the styles on the current Styler. Possibly uses styles from Styler.export. Parameters
styles:dict(str, Any)
List of attributes to add to Styler. Dict keys should contain only:
“apply”: list of styler functions, typically added with apply or ... | pandas.reference.api.pandas.io.formats.style.styler.use |
pandas.io.formats.style.Styler.where Styler.where(cond, value, other=None, subset=None, **kwargs)[source]
Apply CSS-styles based on a conditional function elementwise. Deprecated since version 1.3.0. Updates the HTML representation with a style which is selected in accordance with the return value of a function. ... | pandas.reference.api.pandas.io.formats.style.styler.where |
pandas.io.json.build_table_schema pandas.io.json.build_table_schema(data, index=True, primary_key=None, version=True)[source]
Create a Table schema from data. Parameters
data:Series, DataFrame
index:bool, default True
Whether to include data.index in the schema.
primary_key:bool or None, default True
Co... | pandas.reference.api.pandas.io.json.build_table_schema |
pandas.io.stata.StataReader.data_label propertyStataReader.data_label
Return data label of Stata file. | pandas.reference.api.pandas.io.stata.statareader.data_label |
pandas.io.stata.StataReader.value_labels StataReader.value_labels()[source]
Return a dict, associating each variable name a dict, associating each value its corresponding label. Returns
dict | pandas.reference.api.pandas.io.stata.statareader.value_labels |
pandas.io.stata.StataReader.variable_labels StataReader.variable_labels()[source]
Return variable labels as a dict, associating each variable name with corresponding label. Returns
dict | pandas.reference.api.pandas.io.stata.statareader.variable_labels |
pandas.io.stata.StataWriter.write_file StataWriter.write_file()[source]
Export DataFrame object to Stata dta format. | pandas.reference.api.pandas.io.stata.statawriter.write_file |
pandas.isna pandas.isna(obj)[source]
Detect missing values for an array-like object. This function takes a scalar or array-like object and indicates whether values are missing (NaN in numeric arrays, None or NaN in object arrays, NaT in datetimelike). Parameters
obj:scalar or array-like
Object to check for nu... | pandas.reference.api.pandas.isna |
pandas.isnull pandas.isnull(obj)[source]
Detect missing values for an array-like object. This function takes a scalar or array-like object and indicates whether values are missing (NaN in numeric arrays, None or NaN in object arrays, NaT in datetimelike). Parameters
obj:scalar or array-like
Object to check fo... | pandas.reference.api.pandas.isnull |
pandas.json_normalize pandas.json_normalize(data, record_path=None, meta=None, meta_prefix=None, record_prefix=None, errors='raise', sep='.', max_level=None)[source]
Normalize semi-structured JSON data into a flat table. Parameters
data:dict or list of dicts
Unserialized JSON objects.
record_path:str or lis... | pandas.reference.api.pandas.json_normalize |
pandas.melt pandas.melt(frame, id_vars=None, value_vars=None, var_name=None, value_name='value', col_level=None, ignore_index=True)[source]
Unpivot a DataFrame from wide to long format, optionally leaving identifiers set. This function is useful to massage a DataFrame into a format where one or more columns are ide... | pandas.reference.api.pandas.melt |
pandas.merge pandas.merge(left, right, how='inner', on=None, left_on=None, right_on=None, left_index=False, right_index=False, sort=False, suffixes=('_x', '_y'), copy=True, indicator=False, validate=None)[source]
Merge DataFrame or named Series objects with a database-style join. A named Series object is treated as... | pandas.reference.api.pandas.merge |
pandas.merge_asof pandas.merge_asof(left, right, on=None, left_on=None, right_on=None, left_index=False, right_index=False, by=None, left_by=None, right_by=None, suffixes=('_x', '_y'), tolerance=None, allow_exact_matches=True, direction='backward')[source]
Perform a merge by key distance. This is similar to a left-... | pandas.reference.api.pandas.merge_asof |
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