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pandas.Series.mean Series.mean(axis=NoDefault.no_default, skipna=True, level=None, numeric_only=None, **kwargs)[source]
Return the mean of the values over the requested axis. Parameters
axis:{index (0)}
Axis for the function to be applied on.
skipna:bool, default True
Exclude NA/null values when computing... | pandas.reference.api.pandas.series.mean |
pandas.Series.median Series.median(axis=NoDefault.no_default, skipna=True, level=None, numeric_only=None, **kwargs)[source]
Return the median of the values over the requested axis. Parameters
axis:{index (0)}
Axis for the function to be applied on.
skipna:bool, default True
Exclude NA/null values when com... | pandas.reference.api.pandas.series.median |
pandas.Series.memory_usage Series.memory_usage(index=True, deep=False)[source]
Return the memory usage of the Series. The memory usage can optionally include the contribution of the index and of elements of object dtype. Parameters
index:bool, default True
Specifies whether to include the memory usage of the ... | pandas.reference.api.pandas.series.memory_usage |
pandas.Series.min Series.min(axis=NoDefault.no_default, skipna=True, level=None, numeric_only=None, **kwargs)[source]
Return the minimum of the values over the requested axis. If you want the index of the minimum, use idxmin. This is the equivalent of the numpy.ndarray method argmin. Parameters
axis:{index (0)}... | pandas.reference.api.pandas.series.min |
pandas.Series.mod Series.mod(other, level=None, fill_value=None, axis=0)[source]
Return Modulo of series and other, element-wise (binary operator mod). Equivalent to series % other, but with support to substitute a fill_value for missing data in either one of the inputs. Parameters
other:Series or scalar value
... | pandas.reference.api.pandas.series.mod |
pandas.Series.mode Series.mode(dropna=True)[source]
Return the mode(s) of the Series. The mode is the value that appears most often. There can be multiple modes. Always returns Series even if only one value is returned. Parameters
dropna:bool, default True
Don’t consider counts of NaN/NaT. Returns
Series... | pandas.reference.api.pandas.series.mode |
pandas.Series.mul Series.mul(other, level=None, fill_value=None, axis=0)[source]
Return Multiplication of series and other, element-wise (binary operator mul). Equivalent to series * other, but with support to substitute a fill_value for missing data in either one of the inputs. Parameters
other:Series or scala... | pandas.reference.api.pandas.series.mul |
pandas.Series.multiply Series.multiply(other, level=None, fill_value=None, axis=0)[source]
Return Multiplication of series and other, element-wise (binary operator mul). Equivalent to series * other, but with support to substitute a fill_value for missing data in either one of the inputs. Parameters
other:Serie... | pandas.reference.api.pandas.series.multiply |
pandas.Series.name propertySeries.name
Return the name of the Series. The name of a Series becomes its index or column name if it is used to form a DataFrame. It is also used whenever displaying the Series using the interpreter. Returns
label (hashable object)
The name of the Series, also the column name if par... | pandas.reference.api.pandas.series.name |
pandas.Series.nbytes propertySeries.nbytes
Return the number of bytes in the underlying data. | pandas.reference.api.pandas.series.nbytes |
pandas.Series.ndim propertySeries.ndim
Number of dimensions of the underlying data, by definition 1. | pandas.reference.api.pandas.series.ndim |
pandas.Series.ne Series.ne(other, level=None, fill_value=None, axis=0)[source]
Return Not equal to of series and other, element-wise (binary operator ne). Equivalent to series != other, but with support to substitute a fill_value for missing data in either one of the inputs. Parameters
other:Series or scalar va... | pandas.reference.api.pandas.series.ne |
pandas.Series.nlargest Series.nlargest(n=5, keep='first')[source]
Return the largest n elements. Parameters
n:int, default 5
Return this many descending sorted values.
keep:{‘first’, ‘last’, ‘all’}, default ‘first’
When there are duplicate values that cannot all fit in a Series of n elements: first : ret... | pandas.reference.api.pandas.series.nlargest |
pandas.Series.notna Series.notna()[source]
Detect existing (non-missing) values. Return a boolean same-sized object indicating if the values are not NA. Non-missing values get mapped to True. Characters such as empty strings '' or numpy.inf are not considered NA values (unless you set pandas.options.mode.use_inf_as... | pandas.reference.api.pandas.series.notna |
pandas.Series.notnull Series.notnull()[source]
Series.notnull is an alias for Series.notna. Detect existing (non-missing) values. Return a boolean same-sized object indicating if the values are not NA. Non-missing values get mapped to True. Characters such as empty strings '' or numpy.inf are not considered NA valu... | pandas.reference.api.pandas.series.notnull |
pandas.Series.nsmallest Series.nsmallest(n=5, keep='first')[source]
Return the smallest n elements. Parameters
n:int, default 5
Return this many ascending sorted values.
keep:{‘first’, ‘last’, ‘all’}, default ‘first’
When there are duplicate values that cannot all fit in a Series of n elements: first : r... | pandas.reference.api.pandas.series.nsmallest |
pandas.Series.nunique Series.nunique(dropna=True)[source]
Return number of unique elements in the object. Excludes NA values by default. Parameters
dropna:bool, default True
Don’t include NaN in the count. Returns
int
See also DataFrame.nunique
Method nunique for DataFrame. Series.count
Count non... | pandas.reference.api.pandas.series.nunique |
pandas.Series.pad Series.pad(axis=None, inplace=False, limit=None, downcast=None)[source]
Synonym for DataFrame.fillna() with method='ffill'. Returns
Series/DataFrame or None
Object with missing values filled or None if inplace=True. | pandas.reference.api.pandas.series.pad |
pandas.Series.pct_change Series.pct_change(periods=1, fill_method='pad', limit=None, freq=None, **kwargs)[source]
Percentage change between the current and a prior element. Computes the percentage change from the immediately previous row by default. This is useful in comparing the percentage of change in a time ser... | pandas.reference.api.pandas.series.pct_change |
pandas.Series.pipe Series.pipe(func, *args, **kwargs)[source]
Apply chainable functions that expect Series or DataFrames. Parameters
func:function
Function to apply to the Series/DataFrame. args, and kwargs are passed into func. Alternatively a (callable, data_keyword) tuple where data_keyword is a string ind... | pandas.reference.api.pandas.series.pipe |
pandas.Series.plot Series.plot(*args, **kwargs)[source]
Make plots of Series or DataFrame. Uses the backend specified by the option plotting.backend. By default, matplotlib is used. Parameters
data:Series or DataFrame
The object for which the method is called.
x:label or position, default None
Only used i... | pandas.reference.api.pandas.series.plot |
pandas.Series.plot.area Series.plot.area(x=None, y=None, **kwargs)[source]
Draw a stacked area plot. An area plot displays quantitative data visually. This function wraps the matplotlib area function. Parameters
x:label or position, optional
Coordinates for the X axis. By default uses the index.
y:label or ... | pandas.reference.api.pandas.series.plot.area |
pandas.Series.plot.bar Series.plot.bar(x=None, y=None, **kwargs)[source]
Vertical bar plot. A bar plot is a plot that presents categorical 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 sp... | pandas.reference.api.pandas.series.plot.bar |
pandas.Series.plot.barh Series.plot.barh(x=None, y=None, **kwargs)[source]
Make a horizontal bar plot. A horizontal bar 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 o... | pandas.reference.api.pandas.series.plot.barh |
pandas.Series.plot.box Series.plot.box(by=None, **kwargs)[source]
Make a box plot of the DataFrame columns. A box plot is a method for graphically depicting groups of numerical data through their quartiles. The box extends from the Q1 to Q3 quartile values of the data, with a line at the median (Q2). The whiskers e... | pandas.reference.api.pandas.series.plot.box |
pandas.Series.plot.density Series.plot.density(bw_method=None, ind=None, **kwargs)[source]
Generate Kernel Density Estimate plot using Gaussian kernels. In statistics, kernel density estimation (KDE) is a non-parametric way to estimate the probability density function (PDF) of a random variable. This function uses ... | pandas.reference.api.pandas.series.plot.density |
pandas.Series.plot.hist Series.plot.hist(by=None, bins=10, **kwargs)[source]
Draw one histogram of the DataFrame’s columns. A histogram is a representation of the distribution of data. This function groups the values of all given Series in the DataFrame into bins and draws all bins in one matplotlib.axes.Axes. This... | pandas.reference.api.pandas.series.plot.hist |
pandas.Series.plot.kde Series.plot.kde(bw_method=None, ind=None, **kwargs)[source]
Generate Kernel Density Estimate plot using Gaussian kernels. In statistics, kernel density estimation (KDE) is a non-parametric way to estimate the probability density function (PDF) of a random variable. This function uses Gaussian... | pandas.reference.api.pandas.series.plot.kde |
pandas.Series.plot.line Series.plot.line(x=None, y=None, **kwargs)[source]
Plot Series or DataFrame as lines. This function is useful to plot lines using DataFrame’s values as coordinates. Parameters
x:label or position, optional
Allows plotting of one column versus another. If not specified, the index of the... | pandas.reference.api.pandas.series.plot.line |
pandas.Series.plot.pie Series.plot.pie(**kwargs)[source]
Generate a pie plot. A pie plot is a proportional representation of the numerical data in a column. This function wraps matplotlib.pyplot.pie() for the specified column. If no column reference is passed and subplots=True a pie plot is drawn for each numerical... | pandas.reference.api.pandas.series.plot.pie |
pandas.Series.pop Series.pop(item)[source]
Return item and drops from series. Raise KeyError if not found. Parameters
item:label
Index of the element that needs to be removed. Returns
Value that is popped from series.
Examples
>>> ser = pd.Series([1,2,3])
>>> ser.pop(0)
1
>>> ser
1 2
2 3
... | pandas.reference.api.pandas.series.pop |
pandas.Series.pow Series.pow(other, level=None, fill_value=None, axis=0)[source]
Return Exponential power of series and other, element-wise (binary operator pow). Equivalent to series ** other, but with support to substitute a fill_value for missing data in either one of the inputs. Parameters
other:Series or s... | pandas.reference.api.pandas.series.pow |
pandas.Series.prod Series.prod(axis=None, skipna=True, level=None, numeric_only=None, min_count=0, **kwargs)[source]
Return the product of the values over the requested axis. Parameters
axis:{index (0)}
Axis for the function to be applied on.
skipna:bool, default True
Exclude NA/null values when computing... | pandas.reference.api.pandas.series.prod |
pandas.Series.product Series.product(axis=None, skipna=True, level=None, numeric_only=None, min_count=0, **kwargs)[source]
Return the product of the values over the requested axis. Parameters
axis:{index (0)}
Axis for the function to be applied on.
skipna:bool, default True
Exclude NA/null values when com... | pandas.reference.api.pandas.series.product |
pandas.Series.quantile Series.quantile(q=0.5, interpolation='linear')[source]
Return value at the given quantile. Parameters
q:float or array-like, default 0.5 (50% quantile)
The quantile(s) to compute, which can lie in range: 0 <= q <= 1.
interpolation:{‘linear’, ‘lower’, ‘higher’, ‘midpoint’, ‘nearest’}
... | pandas.reference.api.pandas.series.quantile |
pandas.Series.radd Series.radd(other, level=None, fill_value=None, axis=0)[source]
Return Addition of series and other, element-wise (binary operator radd). Equivalent to other + series, but with support to substitute a fill_value for missing data in either one of the inputs. Parameters
other:Series or scalar v... | pandas.reference.api.pandas.series.radd |
pandas.Series.rank Series.rank(axis=0, method='average', numeric_only=NoDefault.no_default, na_option='keep', ascending=True, pct=False)[source]
Compute numerical data ranks (1 through n) along axis. By default, equal values are assigned a rank that is the average of the ranks of those values. Parameters
axis:{... | pandas.reference.api.pandas.series.rank |
pandas.Series.ravel Series.ravel(order='C')[source]
Return the flattened underlying data as an ndarray. Returns
numpy.ndarray or ndarray-like
Flattened data of the Series. See also numpy.ndarray.ravel
Return a flattened array. | pandas.reference.api.pandas.series.ravel |
pandas.Series.rdiv Series.rdiv(other, level=None, fill_value=None, axis=0)[source]
Return Floating division of series and other, element-wise (binary operator rtruediv). Equivalent to other / series, but with support to substitute a fill_value for missing data in either one of the inputs. Parameters
other:Serie... | pandas.reference.api.pandas.series.rdiv |
pandas.Series.rdivmod Series.rdivmod(other, level=None, fill_value=None, axis=0)[source]
Return Integer division and modulo of series and other, element-wise (binary operator rdivmod). Equivalent to other divmod series, but with support to substitute a fill_value for missing data in either one of the inputs. Param... | pandas.reference.api.pandas.series.rdivmod |
pandas.Series.reindex Series.reindex(*args, **kwargs)[source]
Conform Series to new index with optional filling logic. Places NA/NaN in locations having no value in the previous index. A new object is produced unless the new index is equivalent to the current one and copy=False. Parameters
index:array-like, opt... | pandas.reference.api.pandas.series.reindex |
pandas.Series.reindex_like Series.reindex_like(other, method=None, copy=True, limit=None, tolerance=None)[source]
Return an object with matching indices as other object. Conform the object to the same index on all axes. Optional filling logic, placing NaN in locations having no value in the previous index. A new ob... | pandas.reference.api.pandas.series.reindex_like |
pandas.Series.rename Series.rename(index=None, *, axis=None, copy=True, inplace=False, level=None, errors='ignore')[source]
Alter Series index labels or name. Function / dict values must be unique (1-to-1). Labels not contained in a dict / Series will be left as-is. Extra labels listed don’t throw an error. Alterna... | pandas.reference.api.pandas.series.rename |
pandas.Series.rename_axis Series.rename_axis(mapper=None, index=None, columns=None, axis=None, copy=True, inplace=False)[source]
Set the name of the axis for the index or columns. Parameters
mapper:scalar, list-like, optional
Value to set the axis name attribute.
index, columns:scalar, list-like, dict-like ... | pandas.reference.api.pandas.series.rename_axis |
pandas.Series.reorder_levels Series.reorder_levels(order)[source]
Rearrange index levels using input order. May not drop or duplicate levels. Parameters
order:list of int representing new level order
Reference level by number or key. Returns
type of caller (new object) | pandas.reference.api.pandas.series.reorder_levels |
pandas.Series.repeat Series.repeat(repeats, axis=None)[source]
Repeat elements of a Series. Returns a new Series where each element of the current Series is repeated consecutively a given number of times. Parameters
repeats:int or array of ints
The number of repetitions for each element. This should be a non-... | pandas.reference.api.pandas.series.repeat |
pandas.Series.replace Series.replace(to_replace=None, value=NoDefault.no_default, inplace=False, limit=None, regex=False, method=NoDefault.no_default)[source]
Replace values given in to_replace with value. Values of the Series are replaced with other values dynamically. This differs from updating with .loc or .iloc... | pandas.reference.api.pandas.series.replace |
pandas.Series.resample Series.resample(rule, axis=0, closed=None, label=None, convention='start', kind=None, loffset=None, base=None, on=None, level=None, origin='start_day', offset=None)[source]
Resample time-series data. Convenience method for frequency conversion and resampling of time series. The object must ha... | pandas.reference.api.pandas.series.resample |
pandas.Series.reset_index Series.reset_index(level=None, drop=False, name=NoDefault.no_default, inplace=False)[source]
Generate a new DataFrame or Series with the index reset. This is useful when the index needs to be treated as a column, or when the index is meaningless and needs to be reset to the default before ... | pandas.reference.api.pandas.series.reset_index |
pandas.Series.rfloordiv Series.rfloordiv(other, level=None, fill_value=None, axis=0)[source]
Return Integer division of series and other, element-wise (binary operator rfloordiv). Equivalent to other // series, but with support to substitute a fill_value for missing data in either one of the inputs. Parameters
... | pandas.reference.api.pandas.series.rfloordiv |
pandas.Series.rmod Series.rmod(other, level=None, fill_value=None, axis=0)[source]
Return Modulo of series and other, element-wise (binary operator rmod). Equivalent to other % series, but with support to substitute a fill_value for missing data in either one of the inputs. Parameters
other:Series or scalar val... | pandas.reference.api.pandas.series.rmod |
pandas.Series.rmul Series.rmul(other, level=None, fill_value=None, axis=0)[source]
Return Multiplication of series and other, element-wise (binary operator rmul). Equivalent to other * series, but with support to substitute a fill_value for missing data in either one of the inputs. Parameters
other:Series or sc... | pandas.reference.api.pandas.series.rmul |
pandas.Series.rolling Series.rolling(window, min_periods=None, center=False, win_type=None, on=None, axis=0, closed=None, method='single')[source]
Provide rolling window calculations. Parameters
window:int, offset, or BaseIndexer subclass
Size of the moving window. If an integer, the fixed number of observati... | pandas.reference.api.pandas.series.rolling |
pandas.Series.round Series.round(decimals=0, *args, **kwargs)[source]
Round each value in a Series to the given number of decimals. Parameters
decimals:int, default 0
Number of decimal places to round to. If decimals is negative, it specifies the number of positions to the left of the decimal point. *args, *... | pandas.reference.api.pandas.series.round |
pandas.Series.rpow Series.rpow(other, level=None, fill_value=None, axis=0)[source]
Return Exponential power of series and other, element-wise (binary operator rpow). Equivalent to other ** series, but with support to substitute a fill_value for missing data in either one of the inputs. Parameters
other:Series o... | pandas.reference.api.pandas.series.rpow |
pandas.Series.rsub Series.rsub(other, level=None, fill_value=None, axis=0)[source]
Return Subtraction of series and other, element-wise (binary operator rsub). Equivalent to other - series, but with support to substitute a fill_value for missing data in either one of the inputs. Parameters
other:Series or scala... | pandas.reference.api.pandas.series.rsub |
pandas.Series.rtruediv Series.rtruediv(other, level=None, fill_value=None, axis=0)[source]
Return Floating division of series and other, element-wise (binary operator rtruediv). Equivalent to other / series, but with support to substitute a fill_value for missing data in either one of the inputs. Parameters
oth... | pandas.reference.api.pandas.series.rtruediv |
pandas.Series.sample Series.sample(n=None, frac=None, replace=False, weights=None, random_state=None, axis=None, ignore_index=False)[source]
Return a random sample of items from an axis of object. You can use random_state for reproducibility. Parameters
n:int, optional
Number of items from axis to return. Can... | pandas.reference.api.pandas.series.sample |
pandas.Series.searchsorted Series.searchsorted(value, side='left', sorter=None)[source]
Find indices where elements should be inserted to maintain order. Find the indices into a sorted Series self such that, if the corresponding elements in value were inserted before the indices, the order of self would be preserve... | pandas.reference.api.pandas.series.searchsorted |
pandas.Series.sem Series.sem(axis=None, skipna=True, level=None, ddof=1, numeric_only=None, **kwargs)[source]
Return unbiased standard error of the mean over requested axis. Normalized by N-1 by default. This can be changed using the ddof argument Parameters
axis:{index (0)}
skipna:bool, default True
Exclud... | pandas.reference.api.pandas.series.sem |
pandas.Series.set_axis Series.set_axis(labels, axis=0, inplace=False)[source]
Assign desired index to given axis. Indexes for row labels can be changed by assigning a list-like or Index. Parameters
labels:list-like, Index
The values for the new index.
axis:{0 or ‘index’}, default 0
The axis to update. The... | pandas.reference.api.pandas.series.set_axis |
pandas.Series.set_flags Series.set_flags(*, copy=False, allows_duplicate_labels=None)[source]
Return a new object with updated flags. Parameters
allows_duplicate_labels:bool, optional
Whether the returned object allows duplicate labels. Returns
Series or DataFrame
The same type as the caller. See a... | pandas.reference.api.pandas.series.set_flags |
pandas.Series.shape propertySeries.shape
Return a tuple of the shape of the underlying data. | pandas.reference.api.pandas.series.shape |
pandas.Series.shift Series.shift(periods=1, freq=None, axis=0, fill_value=None)[source]
Shift index by desired number of periods with an optional time freq. When freq is not passed, shift the index without realigning the data. If freq is passed (in this case, the index must be date or datetime, or it will raise a N... | pandas.reference.api.pandas.series.shift |
pandas.Series.size propertySeries.size
Return the number of elements in the underlying data. | pandas.reference.api.pandas.series.size |
pandas.Series.skew Series.skew(axis=NoDefault.no_default, skipna=True, level=None, numeric_only=None, **kwargs)[source]
Return unbiased skew over requested axis. Normalized by N-1. Parameters
axis:{index (0)}
Axis for the function to be applied on.
skipna:bool, default True
Exclude NA/null values when com... | pandas.reference.api.pandas.series.skew |
pandas.Series.slice_shift Series.slice_shift(periods=1, axis=0)[source]
Equivalent to shift without copying data. The shifted data will not include the dropped periods and the shifted axis will be smaller than the original. Deprecated since version 1.2.0: slice_shift is deprecated, use DataFrame/Series.shift inste... | pandas.reference.api.pandas.series.slice_shift |
pandas.Series.sort_index Series.sort_index(axis=0, level=None, ascending=True, inplace=False, kind='quicksort', na_position='last', sort_remaining=True, ignore_index=False, key=None)[source]
Sort Series by index labels. Returns a new Series sorted by label if inplace argument is False, otherwise updates the origina... | pandas.reference.api.pandas.series.sort_index |
pandas.Series.sort_values Series.sort_values(axis=0, ascending=True, inplace=False, kind='quicksort', na_position='last', ignore_index=False, key=None)[source]
Sort by the values. Sort a Series in ascending or descending order by some criterion. Parameters
axis:{0 or ‘index’}, default 0
Axis to direct sorting... | pandas.reference.api.pandas.series.sort_values |
pandas.Series.sparse Series.sparse()[source]
Accessor for SparseSparse from other sparse matrix data types. | pandas.reference.api.pandas.series.sparse |
pandas.Series.sparse.density Series.sparse.density
The percent of non- fill_value points, as decimal. Examples
>>> s = SparseArray([0, 0, 1, 1, 1], fill_value=0)
>>> s.density
0.6 | pandas.reference.api.pandas.series.sparse.density |
pandas.Series.sparse.fill_value Series.sparse.fill_value
Elements in data that are fill_value are not stored. For memory savings, this should be the most common value in the array. | pandas.reference.api.pandas.series.sparse.fill_value |
pandas.Series.sparse.from_coo classmethodSeries.sparse.from_coo(A, dense_index=False)[source]
Create a Series with sparse values from a scipy.sparse.coo_matrix. Parameters
A:scipy.sparse.coo_matrix
dense_index:bool, default False
If False (default), the SparseSeries index consists of only the coords of the ... | pandas.reference.api.pandas.series.sparse.from_coo |
pandas.Series.sparse.npoints Series.sparse.npoints
The number of non- fill_value points. Examples
>>> s = SparseArray([0, 0, 1, 1, 1], fill_value=0)
>>> s.npoints
3 | pandas.reference.api.pandas.series.sparse.npoints |
pandas.Series.sparse.sp_values Series.sparse.sp_values
An ndarray containing the non- fill_value values. Examples
>>> s = SparseArray([0, 0, 1, 0, 2], fill_value=0)
>>> s.sp_values
array([1, 2]) | pandas.reference.api.pandas.series.sparse.sp_values |
pandas.Series.sparse.to_coo Series.sparse.to_coo(row_levels=(0,), column_levels=(1,), sort_labels=False)[source]
Create a scipy.sparse.coo_matrix from a Series with MultiIndex. Use row_levels and column_levels to determine the row and column coordinates respectively. row_levels and column_levels are the names (labe... | pandas.reference.api.pandas.series.sparse.to_coo |
pandas.Series.squeeze Series.squeeze(axis=None)[source]
Squeeze 1 dimensional axis objects into scalars. Series or DataFrames with a single element are squeezed to a scalar. DataFrames with a single column or a single row are squeezed to a Series. Otherwise the object is unchanged. This method is most useful when y... | pandas.reference.api.pandas.series.squeeze |
pandas.Series.std Series.std(axis=None, skipna=True, level=None, ddof=1, numeric_only=None, **kwargs)[source]
Return sample standard deviation over requested axis. Normalized by N-1 by default. This can be changed using the ddof argument. Parameters
axis:{index (0)}
skipna:bool, default True
Exclude NA/null... | pandas.reference.api.pandas.series.std |
pandas.Series.str Series.str()[source]
Vectorized string functions for Series and Index. NAs stay NA unless handled otherwise by a particular method. Patterned after Python’s string methods, with some inspiration from R’s stringr package. Examples
>>> s = pd.Series(["A_Str_Series"])
>>> s
0 A_Str_Series
dtype: ... | pandas.reference.api.pandas.series.str |
pandas.Series.str.capitalize Series.str.capitalize()[source]
Convert strings in the Series/Index to be capitalized. Equivalent to str.capitalize(). Returns
Series or Index of object
See also Series.str.lower
Converts all characters to lowercase. Series.str.upper
Converts all characters to uppercase. Ser... | pandas.reference.api.pandas.series.str.capitalize |
pandas.Series.str.casefold Series.str.casefold()[source]
Convert strings in the Series/Index to be casefolded. New in version 0.25.0. Equivalent to str.casefold(). Returns
Series or Index of object
See also Series.str.lower
Converts all characters to lowercase. Series.str.upper
Converts all characters ... | pandas.reference.api.pandas.series.str.casefold |
pandas.Series.str.cat Series.str.cat(others=None, sep=None, na_rep=None, join='left')[source]
Concatenate strings in the Series/Index with given separator. If others is specified, this function concatenates the Series/Index and elements of others element-wise. If others is not passed, then all values in the Series/... | pandas.reference.api.pandas.series.str.cat |
pandas.Series.str.center Series.str.center(width, fillchar=' ')[source]
Pad left and right side of strings in the Series/Index. Equivalent to str.center(). Parameters
width:int
Minimum width of resulting string; additional characters will be filled with fillchar.
fillchar:str
Additional character for fill... | pandas.reference.api.pandas.series.str.center |
pandas.Series.str.contains Series.str.contains(pat, case=True, flags=0, na=None, regex=True)[source]
Test if pattern or regex is contained within a string of a Series or Index. Return boolean Series or Index based on whether a given pattern or regex is contained within a string of a Series or Index. Parameters
... | pandas.reference.api.pandas.series.str.contains |
pandas.Series.str.count Series.str.count(pat, flags=0)[source]
Count occurrences of pattern in each string of the Series/Index. This function is used to count the number of times a particular regex pattern is repeated in each of the string elements of the Series. Parameters
pat:str
Valid regular expression. ... | pandas.reference.api.pandas.series.str.count |
pandas.Series.str.decode Series.str.decode(encoding, errors='strict')[source]
Decode character string in the Series/Index using indicated encoding. Equivalent to str.decode() in python2 and bytes.decode() in python3. Parameters
encoding:str
errors:str, optional
Returns
Series or Index | pandas.reference.api.pandas.series.str.decode |
pandas.Series.str.encode Series.str.encode(encoding, errors='strict')[source]
Encode character string in the Series/Index using indicated encoding. Equivalent to str.encode(). Parameters
encoding:str
errors:str, optional
Returns
encoded:Series/Index of objects | pandas.reference.api.pandas.series.str.encode |
pandas.Series.str.endswith Series.str.endswith(pat, na=None)[source]
Test if the end of each string element matches a pattern. Equivalent to str.endswith(). Parameters
pat:str
Character sequence. Regular expressions are not accepted.
na:object, default NaN
Object shown if element tested is not a string. T... | pandas.reference.api.pandas.series.str.endswith |
pandas.Series.str.extract Series.str.extract(pat, flags=0, expand=True)[source]
Extract capture groups in the regex pat as columns in a DataFrame. For each subject string in the Series, extract groups from the first match of regular expression pat. Parameters
pat:str
Regular expression pattern with capturing ... | pandas.reference.api.pandas.series.str.extract |
pandas.Series.str.extractall Series.str.extractall(pat, flags=0)[source]
Extract capture groups in the regex pat as columns in 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... | pandas.reference.api.pandas.series.str.extractall |
pandas.Series.str.find Series.str.find(sub, start=0, end=None)[source]
Return lowest indexes in each strings in the Series/Index. Each of returned indexes corresponds to the position where the substring is fully contained between [start:end]. Return -1 on failure. Equivalent to standard str.find(). Parameters
s... | pandas.reference.api.pandas.series.str.find |
pandas.Series.str.findall Series.str.findall(pat, flags=0)[source]
Find all occurrences of pattern or regular expression in the Series/Index. Equivalent to applying re.findall() to all the elements in the Series/Index. Parameters
pat:str
Pattern or regular expression.
flags:int, default 0
Flags from re mo... | pandas.reference.api.pandas.series.str.findall |
pandas.Series.str.fullmatch Series.str.fullmatch(pat, case=True, flags=0, na=None)[source]
Determine if each string entirely matches a regular expression. New in version 1.1.0. Parameters
pat:str
Character sequence or regular expression.
case:bool, default True
If True, case sensitive.
flags:int, defa... | pandas.reference.api.pandas.series.str.fullmatch |
pandas.Series.str.get Series.str.get(i)[source]
Extract element from each component at specified position. Extract element from lists, tuples, or strings in each element in the Series/Index. Parameters
i:int
Position of element to extract. Returns
Series or Index
Examples
>>> s = pd.Series(["String",... | pandas.reference.api.pandas.series.str.get |
pandas.Series.str.get_dummies Series.str.get_dummies(sep='|')[source]
Return DataFrame of dummy/indicator variables for Series. Each string in Series is split by sep and returned as a DataFrame of dummy/indicator variables. Parameters
sep:str, default “|”
String to split on. Returns
DataFrame
Dummy vari... | pandas.reference.api.pandas.series.str.get_dummies |
pandas.Series.str.index Series.str.index(sub, start=0, end=None)[source]
Return lowest indexes in each string in Series/Index. Each of the returned indexes corresponds to the position where the substring is fully contained between [start:end]. This is the same as str.find except instead of returning -1, it raises a... | pandas.reference.api.pandas.series.str.index |
pandas.Series.str.isalnum Series.str.isalnum()[source]
Check whether all characters in each string are alphanumeric. This is equivalent to running the Python string method str.isalnum() for each element of the Series/Index. If a string has zero characters, False is returned for that check. Returns
Series or Inde... | pandas.reference.api.pandas.series.str.isalnum |
pandas.Series.str.isalpha Series.str.isalpha()[source]
Check whether all characters in each string are alphabetic. This is equivalent to running the Python string method str.isalpha() for each element of the Series/Index. If a string has zero characters, False is returned for that check. Returns
Series or Index ... | pandas.reference.api.pandas.series.str.isalpha |
pandas.Series.str.isdecimal Series.str.isdecimal()[source]
Check whether all characters in each string are decimal. This is equivalent to running the Python string method str.isdecimal() for each element of the Series/Index. If a string has zero characters, False is returned for that check. Returns
Series or Ind... | pandas.reference.api.pandas.series.str.isdecimal |
pandas.Series.str.isdigit Series.str.isdigit()[source]
Check whether all characters in each string are digits. This is equivalent to running the Python string method str.isdigit() for each element of the Series/Index. If a string has zero characters, False is returned for that check. Returns
Series or Index of b... | pandas.reference.api.pandas.series.str.isdigit |
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