Class Series (0.3.0)

N-dimensional analogue of DataFrame. Store multi-dimensional in a size-mutable, labeled data structure

Accessor object for datetime-like properties of the Series values.

Return the dtype object of the underlying data.

Return the dtype object of the underlying data.

Indicates whether Series/DataFrame is empty.

True if Series/DataFrame is entirely empty (no items), meaning any of the axes are of length 0.

Purely integer-location based indexing for selection by position.

.iloc[] is primarily integer position based (from 0 to length-1 of the axis), but may also be used with a boolean array.

Allowed inputs are:

• Not supported yetAn integer, e.g. 5 .
• Not supported yetA list or array of integers, e.g. [4, 3, 0] .
• A slice object with ints, e.g. 1:7 .
• Not supported yetA boolean array.
• Not supported yetA callable function with one argument (the calling Series or DataFrame) that returns valid output for indexing (one of the above). This is useful in method chains, when you don't have a reference to the calling object, but would like to base your selection on some value.
• Not supported yetA tuple of row and column indexes. The tuple elements consist of one of the above inputs, e.g. (0, 1) .

.iloc will raise IndexError if a requested indexer is out-of-bounds, except slice indexers which allow out-of-bounds indexing (this conforms with python/numpy slice semantics).

The index (axis labels) of the Series.

Return boolean if values in the object are monotonically decreasing.

Return boolean if values in the object are monotonically increasing.

Access a group of rows and columns by label(s) or a boolean array.

.loc[] is primarily label based, but may also be used with a boolean array.

Allowed inputs are:

• A single label, e.g. 5 or 'a' , (note that 5 is interpreted as a label of the index, and neveras an integer position along the index).
• A list of labels, e.g. ['a', 'b', 'c'] .
• A boolean series of the same length as the axis being sliced, e.g. [True, False, True] .
• An alignable Index. The index of the returned selection will be the input.
• Not supported yetAn alignable boolean Series. The index of the key will be aligned before masking.
• Not supported yetA slice object with labels, e.g. 'a':'f' . Note: contrary to usual python slices, boththe start and the stop are included.
• Not supported yetA callable function with one argument (the calling Series or DataFrame) that returns valid output for indexing (one of the above).

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.

Return an int representing the number of axes / array dimensions.

BigQuery job metadata for the most recent query.

Return a tuple of the shape of the underlying data.

Return an int representing the number of elements in this object.

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.

API documentation for values property.

Used to support numpy ufuncs. See: https://numpy.org/doc/stable/reference/ufuncs.html

Matrix multiplication using binary @ operator in Python>=3.5.

Return a Series/DataFrame with absolute numeric value of each element.

This function only applies to elements that are all numeric.

Return addition of Series and other, element-wise (binary operator add).

Equivalent to series + other , but with support to substitute a fill_value for missing data in either one of the inputs.

Prefix labels with string prefix .

For Series, the row labels are prefixed. For DataFrame, the column labels are prefixed.

Suffix labels with string suffix .

For Series, the row labels are suffixed. For DataFrame, the column labels are suffixed.

Aggregate using one or more operations over the specified axis.

Return whether all elements are True, potentially over an axis.

Returns True unless there at least one element within a Series or along a DataFrame axis that is False or equivalent (e.g. zero or empty).

Return whether any element is True, potentially over an axis.

Returns False unless there is at least one element within a series or along a Dataframe axis that is True or equivalent (e.g. non-zero or non-empty).

Invoke function on values of Series.

Can be ufunc (a NumPy function that applies to the entire Series) or a Python function that only works on single values.

Return int position of the smallest value in the Series.

If the minimum is achieved in multiple locations, the first row position is returned.

Return int position of the largest value in the Series.

If the maximum is achieved in multiple locations, the first row position is returned.

Cast a pandas object to a specified dtype dtype .

Return boolean Series equivalent to left <= series <= right.

This function returns a boolean vector containing True wherever the corresponding Series element is between the boundary values left and right . NA values are treated as False .

Trim values at input threshold(s).

Assigns values outside boundary to boundary values. Thresholds can be singular values or array like, and in the latter case the clipping is performed element-wise in the specified axis.

Make a copy of this object's indices and data.

A new object will be created with a copy of the calling object's data and indices. Modifications to the data or indices of the copy will not be reflected in the original object.

Compute the correlation with the other Series. Non-number values are ignored in the computation.

Uses the "Pearson" method of correlation. Numbers are converted to float before calculation, so the result may be unstable.

Return number of non-NA/null observations in the Series.

Return cumulative maximum over a DataFrame or Series axis.

Returns a DataFrame or Series of the same size containing the cumulative maximum.

Return cumulative minimum over a DataFrame or Series axis.

Returns a DataFrame or Series of the same size containing the cumulative minimum.

Return cumulative product over a DataFrame or Series axis.

Returns a DataFrame or Series of the same size containing the cumulative product.

Return cumulative sum over a DataFrame or Series axis.

Returns a DataFrame or Series of the same size containing the cumulative sum.

First discrete difference of element.

Calculates the difference of a {klass} element compared with another element in the {klass} (default is element in previous row).

Return floating division of Series and other, element-wise (binary operator truediv).

Equivalent to series / other , but with support to substitute a fill_value for missing data in either one of the inputs.

Return floating division of Series and other, element-wise (binary operator truediv).

Equivalent to series / other , but with support to substitute a fill_value for missing data in either one of the inputs.

Return integer division and modulo of Series and other, element-wise (binary operator divmod).

Equivalent to divmod(series, other).

Compute the dot product between the Series and the columns of other.

This method computes the dot product between the Series and another one, or the Series and each columns of a DataFrame, or the Series and each columns of an array.

It can also be called using self @ other in Python >= 3.5.

Return Series with specified index labels removed.

Remove elements of a Series based on specifying the index labels. When using a multi-index, labels on different levels can be removed by specifying the level.

Return Series with duplicate values removed.

Return Series with requested index / column level(s) removed.

Return a new Series with missing values removed.

Indicate duplicate Series values.

Duplicated values are indicated as True values in the resulting Series. Either all duplicates, all except the first or all except the last occurrence of duplicates can be indicated.

Return equal of Series and other, element-wise (binary operator eq).

Equivalent to other == series , but with support to substitute a fill_value for missing data in either one of the inputs.

Provide expanding window calculations.

Fill NA/NaN values using the specified method.

Return integer division of Series and other, element-wise (binary operator floordiv).

Equivalent to series // other , but with support to substitute a fill_value for missing data in either one of the inputs.

Get 'greater than or equal to' of Series and other, element-wise (binary operator >= ).

Equivalent to series >= other , but with support to substitute a fill_value for missing data in either one of the inputs.

Get item from object for given key (ex: DataFrame column).

Returns default value if not found.

Group Series using a mapper or by a Series of columns.

A groupby operation involves some combination of splitting the object, applying a function, and combining the results. This can be used to group large amounts of data and compute operations on these groups.

Get 'less than or equal to' of Series and other, element-wise (binary operator <= ).

Equivalent to series <= other , but with support to substitute a fill_value for missing data in either one of the inputs.

Return the first n rows.

This function returns the first n rows for the object based on position. It is useful for quickly testing if your object has the right type of data in it.

Not yet supportedFor negative values of n , this function returns all rows except the last |n| rows, equivalent to df[:n] .

If n is larger than the number of rows, this function returns all rows.

Whether elements in Series are contained in values.

Return a boolean Series showing whether each element in the Series matches an element in the passed sequence of values exactly.

Detect missing values.

Return a boolean same-sized object indicating if the values are NA. NA values get mapped to True values. Everything else gets mapped to False values. Characters such as empty strings '' or numpy.inf are not considered NA values.

Detect missing values.

Return a boolean same-sized object indicating if the values are NA. NA values get mapped to True values. Everything else gets mapped to False values. Characters such as empty strings '' or numpy.inf are not considered NA values.

Return unbiased kurtosis over requested axis.

Kurtosis obtained using Fisher’s definition of kurtosis (kurtosis of normal == 0.0). Normalized by N-1.

Return unbiased kurtosis over requested axis.

Kurtosis obtained using Fisher’s definition of kurtosis (kurtosis of normal == 0.0). Normalized by N-1.

Get 'less than or equal to' of Series and other, element-wise (binary operator <= ).

Equivalent to series <= other , but with support to substitute a fill_value for missing data in either one of the inputs.

Get 'less than' of Series and other, element-wise (binary operator < ).

Equivalent to series < other , but with support to substitute a fill_value for missing data in either one of the inputs.

Map values of Series according to an input mapping or function.

Used for substituting each value in a Series with another value, that may be derived from a remote function, dict , or a Series .

If arg is a remote function, the overhead for remote functions applies. If mapping with a dict, fully deferred computation is possible. If mapping with a Series, fully deferred computation is only possible if verify_integrity=False.

Replace values where the condition is True.

Return the maximum of the values over the requested axis.

If you want the index of the maximum, use idxmax . This is the equivalent of the numpy.ndarray method argmax .

Return the mean of the values over the requested axis.

Return the median of the values over the requested axis.

Return the maximum 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 .

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.

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.

Return multiplication of Series and other, element-wise (binary operator mul).

Equivalent to other * series , but with support to substitute a fill_value for missing data in either one of the inputs.

Return multiplication of Series and other, element-wise (binary operator mul).

Equivalent to other * series , but with support to substitute a fill_value for missing data in either one of the inputs.

Return not equal of Series and other, element-wise (binary operator ne).

Equivalent to other != series , but with support to substitute a fill_value for missing data in either one of the inputs.

Return the largest n elements.

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. NA values get mapped to False values.

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. NA values get mapped to False values.

Return the smallest n elements.

Return number of unique elements in the object.

Excludes NA values by default.

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.

Return the product of the values over the requested axis.

Return the product of the values over the requested axis.

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.

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.

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.

Return integer division and modulo of Series and other, element-wise (binary operator rdivmod).

Equivalent to other divmod series.

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.

Alternatively, change Series.name with a scalar value.

Set the name of the axis for the index or columns.

Rearrange index levels using input order.

May not drop or duplicate levels.

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 another operation.

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.

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.

Return multiplication of Series and other, element-wise (binary operator mul).

Equivalent to series * others , but with support to substitute a fill_value for missing data in either one of the inputs.

Provide rolling window calculations.

Round each value in a Series to the given number of decimals.

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.

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.

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.

Return a random sample of items from an axis of object.

You can use random_state for reproducibility.

Shift index by desired number of periods.

Shifts the index without realigning the data.

Return unbiased skew over requested axis.

Normalized by N-1.

Sort Series by index labels.

Returns a new Series sorted by label if inplace argument is False , otherwise updates the original series and returns None.

Sort by the values.

Sort a Series in ascending or descending order by some criterion.

Return sample standard deviation over requested axis.

Normalized by N-1 by default.

Return subtraction of Series and other, element-wise (binary operator sub).

Equivalent to series - other , but with support to substitute a fill_value for missing data in either one of the inputs.

Return subtraction of Series and other, element-wise (binary operator sub).

Equivalent to series - other , but with support to substitute a fill_value for missing data in either one of the inputs.

Return the sum of the values over the requested axis.

This is equivalent to the method numpy.sum .

Return the last n rows.

This function returns last n rows from the object based on 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.

Write object to a comma-separated values (csv) file.

Convert Series to {label -> value} dict or dict-like object.

Write Series to an Excel sheet.

To write a single Series to an Excel .xlsx file it is only necessary to specify a target file name. To write to multiple sheets it is necessary to create an ExcelWriter object with a target file name, and specify a sheet in the file to write to.

Multiple sheets may be written to by specifying unique sheet_name . With all data written to the file it is necessary to save the changes. Note that creating an ExcelWriter object with a file name that already exists will result in the contents of the existing file being erased.

Convert Series to DataFrame.

The column in the new dataframe will be named name (the keyword parameter) if the name parameter is provided and not None.

Convert the object to a JSON string.

Note NaN's and None will be converted to null and datetime objects will be converted to UNIX timestamps.

Render object to a LaTeX tabular, longtable, or nested table.

Return a list of the values.

These are each a scalar type, which is a Python scalar (for str, int, float) or a pandas scalar (for Timestamp/Timedelta/Interval/Period).

Print {klass} in Markdown-friendly format.

A NumPy ndarray representing the values in this Series or Index.

Writes Series to pandas Series.

Pickle (serialize) object to file.

Render a string representation of the Series.

Return an xarray object from the pandas object.

Return a list of the values.

These are each a scalar type, which is a Python scalar (for str, int, float) or a pandas scalar (for Timestamp/Timedelta/Interval/Period).

Return floating division of Series and other, element-wise (binary operator truediv).

Equivalent to series / other , but with support to substitute a fill_value for missing data in either one of the inputs.

API documentation for unique method.

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 default.

Return unbiased variance over requested axis.

Normalized by N-1 by default.

Replace values where the condition is False.