# pandas.Series

class `pandas.``Series`(data=None, index=None, dtype=None, name=None, copy=False, fastpath=False)

  One-dimensional ndarray with axis labels (including time series).

  Labels need not be unique but must be a hashable type. The object supports both integer- and label-based indexing and provides a host of methods for performing operations involving the index. Statistical methods from ndarray have been overridden to automatically exclude missing data (currently represented as NaN).

  Operations between Series (+, -, /, , *) align values based on their associated index values– they need not be the same length. The result index will be the sorted union of the two indexes.

  Parameters:

  data : array-like, Iterable, dict, or scalar value

  > Contains data stored in Series.

  > Changed in version 0.23.0: If data is a dict, argument order is maintained for Python 3.6 and later.

  index : array-like or Index (1d)

  > Values must be hashable and have the same length as data. Non-unique index values are allowed. Will default to RangeIndex (0, 1, 2, …, n) if not provided. If both a dict and index sequence are used, the index will override the keys found in the dict.

  dtype : str, numpy.dtype, or ExtensionDtype, optional

  > Data type for the output Series. If not specified, this will be inferred from data. See the user guide for more usages.

  copy : bool, default False

  > Copy input data.

  Attributes

  `T` | Return the transpose, which is by
  `array` | The ExtensionArray of the data backing this Series or Index.
  `asobject` | Return object Series which contains boxed values.
  `at` | Access a single value for a row/column label pair.
  `axes` | Return a list of the row axis labels.
  `base` | (DEPRECATED) Return the base object if the memory of the underlying data is shared.
  `blocks` | (DEPRECATED) Internal property, property synonym for as_blocks().
  `data` | (DEPRECATED) Return the data pointer of the underlying data.
  `dtype` | Return the dtype object of the underlying data.
  `dtypes` | Return the dtype object of the underlying data.
  `empty` |
  `flags` | (DEPRECATED)
  `ftype` | (DEPRECATED) Return if the data is sparse|dense.
  `ftypes` | (DEPRECATED) Return if the data is sparse|dense.
  `hasnans` | Return if I have any nans; enables various perf speedups.
  `iat` | Access a single value for a row/column pair by integer position.
  `iloc` | Purely integer-location based indexing for selection by position.
  `imag` | Return imag value of vector.
  `is_copy` | Return the copy.
  `is_monotonic` | Return boolean if values in the object are monotonic_increasing.
  `is_monotonic_decreasing` | Return boolean if values in the object are monotonic_decreasing.
  `is_monotonic_increasing` | Return boolean if values in the object are monotonic_increasing.
  `is_unique` | Return boolean if values in the object are unique.
  `itemsize` | (DEPRECATED) Return the size of the dtype of the item of the underlying data.
  `ix` | A primarily label-location based indexer, with integer position fallback.
  `loc` | Access a group of rows and columns by label(s) or a boolean array.
  `name` | Return name of the Series.
  `nbytes` | Return the number of bytes in the underlying data.
  `ndim` | Number of dimensions of the underlying data, by definition 1.
  `real` | Return the real value of vector.
  `shape` | Return a tuple of the shape of the underlying data.
  `size` | Return the number of elements in the underlying data.
  `strides` | (DEPRECATED) Return the strides of the underlying data.
  `values` | Return Series as ndarray or ndarray-like depending on the dtype.

  Methods

  `abs`() | Return a Series/DataFrame with absolute numeric value of each element.
  `add`(other[, level, fill_value, axis]) | Return Addition of series and other, element-wise (binary operator add).
  `add_prefix`(prefix) | Prefix labels with string prefix.
  `add_suffix`(suffix) | Suffix labels with string suffix.
  `agg`(func[, axis]) | Aggregate using one or more operations over the specified axis.
  `aggregate`(func[, axis]) | Aggregate using one or more operations over the specified axis.
  `align`(other[, join, axis, level, copy, …]) | Align two objects on their axes with the specified join method for each axis Index.
  `all`([axis, bool_only, skipna, level]) | Return whether all elements are True, potentially over an axis.
  `any`([axis, bool_only, skipna, level]) | Return whether any element is True, potentially over an axis.
  `append`(to_append[, ignore_index, …]) | Concatenate two or more Series.
  `apply`(func[, convert_dtype, args]) | Invoke function on values of Series.
  `argmax`([axis, skipna]) | (DEPRECATED) Return the row label of the maximum value.
  `argmin`([axis, skipna]) | (DEPRECATED) Return the row label of the minimum value.
  `argsort`([axis, kind, order]) | Override ndarray.argsort.
  `as_blocks`([copy]) | (DEPRECATED) Convert the frame to a dict of dtype -> Constructor Types that each has a homogeneous dtype.
  `as_matrix`([columns]) | (DEPRECATED) Convert the frame to its Numpy-array representation.
  `asfreq`(freq[, method, how, normalize, …]) | Convert TimeSeries to specified frequency.
  `asof`(where[, subset]) | Return the last row(s) without any NaNs before where.
  `astype`(dtype[, copy, errors]) | Cast a pandas object to a specified dtype `dtype`.
  `at_time`(time[, asof, axis]) | Select values at particular time of day (e.g.
  `autocorr`([lag]) | Compute the lag-N autocorrelation.
  `between`(left, right[, inclusive]) | Return boolean Series equivalent to left <= series <= right.
  `between_time`(start_time, end_time[, …]) | Select values between particular times of the day (e.g., 9:00-9:30 AM).
  `bfill`([axis, inplace, limit, downcast]) | Synonym for `DataFrame.fillna()` with `method='bfill'`.
  `bool`() | Return the bool of a single element PandasObject.
  `cat` | alias of `pandas.core.arrays.categorical.CategoricalAccessor`
  `clip`([lower, upper, axis, inplace]) | Trim values at input threshold(s).
  `clip_lower`(threshold[, axis, inplace]) | (DEPRECATED) Trim values below a given threshold.
  `clip_upper`(threshold[, axis, inplace]) | (DEPRECATED) Trim values above a given threshold.
  `combine`(other, func[, fill_value]) | Combine the Series with a Series or scalar according to func.
  `combine_first`(other) | Combine Series values, choosing the calling Series’s values first.
  `compound`([axis, skipna, level]) | (DEPRECATED) Return the compound percentage of the values for the requested axis.
  `compress`(condition, *args, **kwargs) | (DEPRECATED) Return selected slices of an array along given axis as a Series.
  `copy`([deep]) | Make a copy of this object’s indices and data.
  `corr`(other[, method, min_periods]) | Compute correlation with other Series, excluding missing values.
  `count`([level]) | Return number of non-NA/null observations in the Series.
  `cov`(other[, min_periods]) | Compute covariance with Series, excluding missing values.
  `cummax`([axis, skipna]) | Return cumulative maximum over a DataFrame or Series axis.
  `cummin`([axis, skipna]) | Return cumulative minimum over a DataFrame or Series axis.
  `cumprod`([axis, skipna]) | Return cumulative product over a DataFrame or Series axis.
  `cumsum`([axis, skipna]) | Return cumulative sum over a DataFrame or Series axis.
  `describe`([percentiles, include, exclude]) | Generate descriptive statistics that summarize the central tendency, dispersion and shape of a dataset’s distribution, excluding `NaN` values.
  `diff`([periods]) | First discrete difference of element.
  `div`(other[, level, fill_value, axis]) | Return Floating division of series and other, element-wise (binary operator truediv).
  `divide`(other[, level, fill_value, axis]) | Return Floating division of series and other, element-wise (binary operator truediv).
  `divmod`(other[, level, fill_value, axis]) | Return Integer division and modulo of series and other, element-wise (binary operator divmod).
  `dot`(other) | Compute the dot product between the Series and the columns of other.
  `drop`([labels, axis, index, columns, level, …]) | Return Series with specified index labels removed.
  `drop_duplicates`([keep, inplace]) | Return Series with duplicate values removed.
  `droplevel`(level[, axis]) | Return DataFrame with requested index / column level(s) removed.
  `dropna`([axis, inplace]) | Return a new Series with missing values removed.
  `dt` | alias of `pandas.core.indexes.accessors.CombinedDatetimelikeProperties`
  `duplicated`([keep]) | Indicate duplicate Series values.
  `eq`(other[, level, fill_value, axis]) | Return Equal to of series and other, element-wise (binary operator eq).
  `equals`(other) | Test whether two objects contain the same elements.
  `ewm`([com, span, halflife, alpha, …]) | Provide exponential weighted functions.
  `expanding`([min_periods, center, axis]) | Provide expanding transformations.
  `explode`() | Transform each element of a list-like to a row, replicating the index values.
  `factorize`([sort, na_sentinel]) | Encode the object as an enumerated type or categorical variable.
  `ffill`([axis, inplace, limit, downcast]) | Synonym for `DataFrame.fillna()` with `method='ffill'`.
  `fillna`([value, method, axis, inplace, …]) | Fill NA/NaN values using the specified method.
  `filter`([items, like, regex, axis]) | Subset rows or columns of dataframe according to labels in the specified index.
  `first`(offset) | Convenience method for subsetting initial periods of time series data based on a date offset.
  `first_valid_index`() | Return index for first non-NA/null value.
  `floordiv`(other[, level, fill_value, axis]) | Return Integer division of series and other, element-wise (binary operator floordiv).
  `from_array`(arr[, index, name, dtype, copy, …]) | Construct Series from array.
  `ge`(other[, level, fill_value, axis]) | Return Greater than or equal to of series and other, element-wise (binary operator ge).
  `get`(key[, default]) | Get item from object for given key (ex: DataFrame column).
  `get_dtype_counts`() | (DEPRECATED) Return counts of unique dtypes in this object.
  `get_ftype_counts`() | (DEPRECATED) Return counts of unique ftypes in this object.
  `get_value`(label[, takeable]) | (DEPRECATED) Quickly retrieve single value at passed index label.
  `get_values`() | (DEPRECATED) Same as values (but handles sparseness conversions); is a view.
  `groupby`([by, axis, level, as_index, sort, …]) | Group DataFrame or Series using a mapper or by a Series of columns.
  `gt`(other[, level, fill_value, axis]) | Return Greater than of series and other, element-wise (binary operator gt).
  `head`([n]) | Return the first n rows.
  `hist`([by, ax, grid, xlabelsize, xrot, …]) | Draw histogram of the input series using matplotlib.
  `idxmax`([axis, skipna]) | Return the row label of the maximum value.
  `idxmin`([axis, skipna]) | Return the row label of the minimum value.
  `infer_objects`() | Attempt to infer better dtypes for object columns.
  `interpolate`([method, axis, limit, inplace, …]) | Interpolate values according to different methods.
  `isin`(values) | Check whether values are contained in Series.
  `isna`() | Detect missing values.
  `isnull`() | Detect missing values.
  `item`() | Return the first element of the underlying data as a python scalar.
  `items`() | Lazily iterate over (index, value) tuples.
  `iteritems`() | Lazily iterate over (index, value) tuples.
  `keys`() | Return alias for index.
  `kurt`([axis, skipna, level, numeric_only]) | Return unbiased kurtosis over requested axis using Fisher’s definition of kurtosis (kurtosis of normal == 0.0).
  `kurtosis`([axis, skipna, level, numeric_only]) | Return unbiased kurtosis over requested axis using Fisher’s definition of kurtosis (kurtosis of normal == 0.0).
  `last`(offset) | Convenience method for subsetting final periods of time series data based on a date offset.
  `last_valid_index`() | Return index for last non-NA/null value.
  `le`(other[, level, fill_value, axis]) | Return Less than or equal to of series and other, element-wise (binary operator le).
  `lt`(other[, level, fill_value, axis]) | Return Less than of series and other, element-wise (binary operator lt).
  `mad`([axis, skipna, level]) | Return the mean absolute deviation of the values for the requested axis.
  `map`(arg[, na_action]) | Map values of Series according to input correspondence.
  `mask`(cond[, other, inplace, axis, level, …]) | Replace values where the condition is True.
  `max`([axis, skipna, level, numeric_only]) | Return the maximum of the values for the requested axis.
  `mean`([axis, skipna, level, numeric_only]) | Return the mean of the values for the requested axis.
  `median`([axis, skipna, level, numeric_only]) | Return the median of the values for the requested axis.
  `memory_usage`([index, deep]) | Return the memory usage of the Series.
  `min`([axis, skipna, level, numeric_only]) | Return the minimum of the values for the requested axis.
  `mod`(other[, level, fill_value, axis]) | Return Modulo of series and other, element-wise (binary operator mod).
  `mode`([dropna]) | Return the mode(s) of the dataset.
  `mul`(other[, level, fill_value, axis]) | Return Multiplication of series and other, element-wise (binary operator mul).
  `multiply`(other[, level, fill_value, axis]) | Return Multiplication of series and other, element-wise (binary operator mul).
  `ne`(other[, level, fill_value, axis]) | Return Not equal to of series and other, element-wise (binary operator ne).
  `nlargest`([n, keep]) | Return the largest n elements.
  `nonzero`() | (DEPRECATED) Return the integer indices of the elements that are non-zero.
  `notna`() | Detect existing (non-missing) values.
  `notnull`() | Detect existing (non-missing) values.
  `nsmallest`([n, keep]) | Return the smallest n elements.
  `nunique`([dropna]) | Return number of unique elements in the object.
  `pct_change`([periods, fill_method, limit, freq]) | Percentage change between the current and a prior element.
  `pipe`(func, *args, **kwargs) | Apply func(self, *args, **kwargs).
  `plot` | alias of `pandas.plotting._core.PlotAccessor`
  `pop`(item) | Return item and drop from frame.
  `pow`(other[, level, fill_value, axis]) | Return Exponential power of series and other, element-wise (binary operator pow).
  `prod`([axis, skipna, level, numeric_only, …]) | Return the product of the values for the requested axis.
  `product`([axis, skipna, level, numeric_only, …]) | Return the product of the values for the requested axis.
  `ptp`([axis, skipna, level, numeric_only]) | (DEPRECATED) Return the difference between the maximum value and the
  `put`(*args, **kwargs) | (DEPRECATED) Apply the put method to its values attribute if it has one.
  `quantile`([q, interpolation]) | Return value at the given quantile.
  `radd`(other[, level, fill_value, axis]) | Return Addition of series and other, element-wise (binary operator radd).
  `rank`([axis, method, numeric_only, …]) | Compute numerical data ranks (1 through n) along axis.
  `ravel`([order]) | Return the flattened underlying data as an ndarray.
  `rdiv`(other[, level, fill_value, axis]) | Return Floating division of series and other, element-wise (binary operator rtruediv).
  `rdivmod`(other[, level, fill_value, axis]) | Return Integer division and modulo of series and other, element-wise (binary operator rdivmod).
  `reindex`([index]) | Conform Series to new index with optional filling logic, placing NA/NaN in locations having no value in the previous index.
  `reindex_like`(other[, method, copy, limit, …]) | Return an object with matching indices as other object.
  `rename`([index]) | Alter Series index labels or name.
  `rename_axis`([mapper, index, columns, axis, …]) | Set the name of the axis for the index or columns.
  `reorder_levels`(order) | Rearrange index levels using input order.
  `repeat`(repeats[, axis]) | Repeat elements of a Series.
  `replace`([to_replace, value, inplace, limit, …]) | Replace values given in to_replace with value.
  `resample`(rule[, how, axis, fill_method, …]) | Resample time-series data.
  `reset_index`([level, drop, name, inplace]) | Generate a new DataFrame or Series with the index reset.
  `rfloordiv`(other[, level, fill_value, axis]) | Return Integer division of series and other, element-wise (binary operator rfloordiv).
  `rmod`(other[, level, fill_value, axis]) | Return Modulo of series and other, element-wise (binary operator rmod).
  `rmul`(other[, level, fill_value, axis]) | Return Multiplication of series and other, element-wise (binary operator rmul).
  `rolling`(window[, min_periods, center, …]) | Provide rolling window calculations.
  `round`([decimals]) | Round each value in a Series to the given number of decimals.
  `rpow`(other[, level, fill_value, axis]) | Return Exponential power of series and other, element-wise (binary operator rpow).
  `rsub`(other[, level, fill_value, axis]) | Return Subtraction of series and other, element-wise (binary operator rsub).
  `rtruediv`(other[, level, fill_value, axis]) | Return Floating division of series and other, element-wise (binary operator rtruediv).
  `sample`([n, frac, replace, weights, …]) | Return a random sample of items from an axis of object.
  `searchsorted`(value[, side, sorter]) | Find indices where elements should be inserted to maintain order.
  `sem`([axis, skipna, level, ddof, numeric_only]) | Return unbiased standard error of the mean over requested axis.
  `set_axis`(labels[, axis, inplace]) | Assign desired index to given axis.
  `set_value`(label, value[, takeable]) | (DEPRECATED) Quickly set single value at passed label.
  `shift`([periods, freq, axis, fill_value]) | Shift index by desired number of periods with an optional time freq.
  `skew`([axis, skipna, level, numeric_only]) | Return unbiased skew over requested axis Normalized by N-1.
  `slice_shift`([periods, axis]) | Equivalent to shift without copying data.
  `sort_index`([axis, level, ascending, …]) | Sort Series by index labels.
  `sort_values`([axis, ascending, inplace, …]) | Sort by the values.
  `sparse` | alias of `pandas.core.arrays.sparse.SparseAccessor`
  `squeeze`([axis]) | Squeeze 1 dimensional axis objects into scalars.
  `std`([axis, skipna, level, ddof, numeric_only]) | Return sample standard deviation over requested axis.
  `str` | alias of `pandas.core.strings.StringMethods`
  `sub`(other[, level, fill_value, axis]) | Return Subtraction of series and other, element-wise (binary operator sub).
  `subtract`(other[, level, fill_value, axis]) | Return Subtraction of series and other, element-wise (binary operator sub).
  `sum`([axis, skipna, level, numeric_only, …]) | Return the sum of the values for the requested axis.
  `swapaxes`(axis1, axis2[, copy]) | Interchange axes and swap values axes appropriately.
  `swaplevel`([i, j, copy]) | Swap levels i and j in a MultiIndex.
  `tail`([n]) | Return the last n rows.
  `take`(indices[, axis, is_copy]) | Return the elements in the given positional indices along an axis.
  `to_clipboard`([excel, sep]) | Copy object to the system clipboard.
  `to_csv`(*args, **kwargs) | Write object to a comma-separated values (csv) file.
  `to_dense`() | (DEPRECATED) Return dense representation of Series/DataFrame (as opposed to sparse).
  `to_dict`([into]) | Convert Series to {label -> value} dict or dict-like object.
  `to_excel`(excel_writer[, sheet_name, na_rep, …]) | Write object to an Excel sheet.
  `to_frame`([name]) | Convert Series to DataFrame.
  `to_hdf`(path_or_buf, key, **kwargs) | Write the contained data to an HDF5 file using HDFStore.
  `to_json`([path_or_buf, orient, date_format, …]) | Convert the object to a JSON string.
  `to_latex`([buf, columns, col_space, header, …]) | Render an object to a LaTeX tabular environment table.
  `to_list`() | Return a list of the values.
  `to_msgpack`([path_or_buf, encoding]) | (DEPRECATED) Serialize object to input file path using msgpack format.
  `to_numpy`([dtype, copy]) | A NumPy ndarray representing the values in this Series or Index.
  `to_period`([freq, copy]) | Convert Series from DatetimeIndex to PeriodIndex with desired frequency (inferred from index if not passed).
  `to_pickle`(path[, compression, protocol]) | Pickle (serialize) object to file.
  `to_sparse`([kind, fill_value]) | (DEPRECATED) Convert Series to SparseSeries.
  `to_sql`(name, con[, schema, if_exists, …]) | Write records stored in a DataFrame to a SQL database.
  `to_string`([buf, na_rep, float_format, …]) | Render a string representation of the Series.
  `to_timestamp`([freq, how, copy]) | Cast to DatetimeIndex of Timestamps, at beginning of period.
  `to_xarray`() | Return an xarray object from the pandas object.
  `tolist`() | Return a list of the values.
  `transform`(func[, axis]) | Call `func` on self producing a Series with transformed values and that has the same axis length as self.
  `transpose`(*args, **kwargs) | Return the transpose, which is by definition self.
  `truediv`(other[, level, fill_value, axis]) | Return Floating division of series and other, element-wise (binary operator truediv).
  `truncate`([before, after, axis, copy]) | Truncate a Series or DataFrame before and after some index value.
  `tshift`([periods, freq, axis]) | Shift the time index, using the index’s frequency if available.
  `tz_convert`(tz[, axis, level, copy]) | Convert tz-aware axis to target time zone.
  `tz_localize`(tz[, axis, level, copy, …]) | Localize tz-naive index of a Series or DataFrame to target time zone.
  `unique`() | Return unique values of Series object.
  `unstack`([level, fill_value]) | Unstack, a.k.a.
  `update`(other) | Modify Series in place using non-NA values from passed Series.
  `valid`([inplace]) | (DEPRECATED) Return Series without null values.
  `value_counts`([normalize, sort, ascending, …]) | Return a Series containing counts of unique values.
  `var`([axis, skipna, level, ddof, numeric_only]) | Return unbiased variance over requested axis.
  `view`([dtype]) | Create a new view of the Series.
  `where`(cond[, other, inplace, axis, level, …]) | Replace values where the condition is False.
  `xs`(key[, axis, level, drop_level]) | Return cross-section from the Series/DataFrame.

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