| S.N | Method | Meaning |
| 1 | abs() | Return a Series/DataFrame with absolute numeric value of each element. |
| 2 | add(other[, level, fill_value, axis]) | Return Addition of series and other, element-wise (binary operator add). |
| 3 | add_prefix(prefix) | Prefix labels with string prefix. |
| 4 | add_suffix(suffix) | Suffix labels with string suffix. |
| 5 | agg([func, axis]) | Aggregate using one or more operations over the specified axis. |
| 6 | aggregate([func, axis]) | Aggregate using one or more operations over the specified axis. |
| 7 | align(other[, join, axis, level, copy, …]) | Align two objects on their axes with the specified join method. |
| 8 | all([axis, bool_only, skipna, level]) | Return whether all elements are True, potentially over an axis. |
| 9 | any([axis, bool_only, skipna, level]) | Return whether any element is True, potentially over an axis. |
| 10 | append(to_append[, ignore_index, …]) | Concatenate two or more Series. |
| 11 | apply(func[, convert_dtype, args]) | Invoke function on values of Series. |
| 12 | argmax([axis, skipna]) | Return int position of the largest value in the Series. |
| 13 | argmin([axis, skipna]) | Return int position of the smallest value in the Series. |
| 14 | argsort([axis, kind, order]) | Return the integer indices that would sort the Series values. |
| 15 | asfreq(freq[, method, how, normalize, …]) | Convert TimeSeries to specified frequency. |
| 16 | asof(where[, subset]) | Return the last row(s) without any NaNs before where. |
| 17 | astype(dtype[, copy, errors]) | Cast a pandas object to a specified dtype dtype. |
| 18 | at_time(time[, asof, axis]) | Select values at particular time of day (e.g., 9:30AM). |
| 19 | autocorr([lag]) | Compute the lag-N autocorrelation. |
| 20 | backfill([axis, inplace, limit, downcast]) | Synonym for DataFrame.fillna() with method='bfill'. |
| 21 | between(left, right[, inclusive]) | Return boolean Series equivalent to left <= series <= right. |
| 22 | between_time(start_time, end_time[, …]) | Select values between particular times of the day (e.g., 9:00-9:30 AM). |
| 23 | bfill([axis, inplace, limit, downcast]) | Synonym for DataFrame.fillna() with method='bfill'. |
| 24 | bool() | Return the bool of a single element Series or DataFrame. |
| 25 | cat | alias of pandas.core.arrays.categorical.CategoricalAccessor |
| 26 | clip([lower, upper, axis, inplace]) | Trim values at input threshold(s). |
| 27 | combine(other, func[, fill_value]) | Combine the Series with a Series or scalar according to func. |
| 28 | combine_first(other) | Combine Series values, choosing the calling Series’s values first. |
| 29 | compare(other[, align_axis, keep_shape, …]) | Compare to another Series and show the differences. |
| 30 | convert_dtypes([infer_objects, …]) | Convert columns to best possible dtypes using dtypes supporting pd.NA. |
| 31 | copy([deep]) | Make a copy of this object’s indices and data. |
| 32 | corr(other[, method, min_periods]) | Compute correlation with other Series, excluding missing values. |
| 33 | count([level]) | Return number of non-NA/null observations in the Series. |
| 34 | cov(other[, min_periods, ddof]) | Compute covariance with Series, excluding missing values. |
| 35 | cummax([axis, skipna]) | Return cumulative maximum over a DataFrame or Series axis. |
| 36 | cummin([axis, skipna]) | Return cumulative minimum over a DataFrame or Series axis. |
| 37 | cumprod([axis, skipna]) | Return cumulative product over a DataFrame or Series axis. |
| 38 | cumsum([axis, skipna]) | Return cumulative sum over a DataFrame or Series axis. |
| 39 | describe([percentiles, include, exclude, …]) | Generate descriptive statistics. |
| 40 | diff([periods]) | First discrete difference of element. |
| 41 | div(other[, level, fill_value, axis]) | Return Floating division of series and other, element-wise (binary operator truediv). |
| 42 | divide(other[, level, fill_value, axis]) | Return Floating division of series and other, element-wise (binary operator truediv). |
| 43 | divmod(other[, level, fill_value, axis]) | Return Integer division and modulo of series and other, element-wise (binary operator divmod). |
| 44 | dot(other) | Compute the dot product between the Series and the columns of other. |
| 45 | drop([labels, axis, index, columns, level, …]) | Return Series with specified index labels removed. |
| 46 | drop_duplicates([keep, inplace]) | Return Series with duplicate values removed. |
| 47 | droplevel(level[, axis]) | Return DataFrame with requested index / column level(s) removed. |
| 48 | dropna([axis, inplace, how]) | Return a new Series with missing values removed. |
| 49 | dt | alias of pandas.core.indexes.accessors.CombinedDatetimelikeProperties |
| 50 | duplicated([keep]) | Indicate duplicate Series values. |
| 51 | eq(other[, level, fill_value, axis]) | Return Equal to of series and other, element-wise (binary operator eq). |
| 52 | equals(other) | Test whether two objects contain the same elements. |
| 53 | ewm([com, span, halflife, alpha, …]) | Provide exponential weighted (EW) functions. |
| 54 | expanding([min_periods, center, axis]) | Provide expanding transformations. |
| 55 | explode([ignore_index]) | Transform each element of a list-like to a row. |
| 56 | factorize([sort, na_sentinel]) | Encode the object as an enumerated type or categorical variable. |
| 57 | ffill([axis, inplace, limit, downcast]) | Synonym for DataFrame.fillna() with method='ffill'. |
| 58 | fillna([value, method, axis, inplace, …]) | Fill NA/NaN values using the specified method. |
| 59 | filter([items, like, regex, axis]) | Subset the dataframe rows or columns according to the specified index labels. |
| 60 | first(offset) | Select initial periods of time series data based on a date offset. |
| 61 | first_valid_index() | Return index for first non-NA/null value. |
| 62 | floordiv(other[, level, fill_value, axis]) | Return Integer division of series and other, element-wise (binary operator floordiv). |
| 63 | ge(other[, level, fill_value, axis]) | Return Greater than or equal to of series and other, element-wise (binary operator ge). |
| 64 | get(key[, default]) | Get item from object for given key (ex: DataFrame column). |
| 65 | groupby([by, axis, level, as_index, sort, …]) | Group Series using a mapper or by a Series of columns. |
| 66 | gt(other[, level, fill_value, axis]) | Return Greater than of series and other, element-wise (binary operator gt). |
| 67 | head([n]) | Return the first n rows. |
| 68 | hist([by, ax, grid, xlabelsize, xrot, …]) | Draw histogram of the input series using matplotlib. |
| 69 | idxmax([axis, skipna]) | Return the row label of the maximum value. |
| 70 | idxmin([axis, skipna]) | Return the row label of the minimum value. |
| 71 | infer_objects() | Attempt to infer better dtypes for object columns. |
| 72 | interpolate([method, axis, limit, inplace, …]) | Fill NaN values using an interpolation method. |
| 73 | isin(values) | Whether elements in Series are contained in values. |
| 74 | isna() | Detect missing values. |
| 75 | isnull() | Detect missing values. |
| 76 | item() | Return the first element of the underlying data as a Python scalar. |
| 77 | items() | Lazily iterate over (index, value) tuples. |
| 78 | iteritems() | Lazily iterate over (index, value) tuples. |
| 79 | keys() | Return alias for index. |
| 80 | kurt([axis, skipna, level, numeric_only]) | Return unbiased kurtosis over requested axis. |
| 81 | kurtosis([axis, skipna, level, numeric_only]) | Return unbiased kurtosis over requested axis. |
| 82 | last(offset) | Select final periods of time series data based on a date offset. |
| 83 | last_valid_index() | Return index for last non-NA/null value. |
| 84 | le(other[, level, fill_value, axis]) | Return Less than or equal to of series and other, element-wise (binary operator le). |
| 85 | lt(other[, level, fill_value, axis]) | Return Less than of series and other, element-wise (binary operator lt). |
| 86 | mad([axis, skipna, level]) | Return the mean absolute deviation of the values over the requested axis. |
| 87 | map(arg[, na_action]) | Map values of Series according to input correspondence. |
| 88 | mask(cond[, other, inplace, axis, level, …]) | Replace values where the condition is True. |
| 89 | max([axis, skipna, level, numeric_only]) | Return the maximum of the values over the requested axis. |
| 90 | mean([axis, skipna, level, numeric_only]) | Return the mean of the values over the requested axis. |
| 91 | median([axis, skipna, level, numeric_only]) | Return the median of the values over the requested axis. |
| 92 | memory_usage([index, deep]) | Return the memory usage of the Series. |
| 93 | min([axis, skipna, level, numeric_only]) | Return the minimum of the values over the requested axis. |
| 94 | mod(other[, level, fill_value, axis]) | Return Modulo of series and other, element-wise (binary operator mod). |
| 95 | mode([dropna]) | Return the mode(s) of the Series. |
| 96 | mul(other[, level, fill_value, axis]) | Return Multiplication of series and other, element-wise (binary operator mul). |
| 97 | multiply(other[, level, fill_value, axis]) | Return Multiplication of series and other, element-wise (binary operator mul). |
| 98 | ne(other[, level, fill_value, axis]) | Return Not equal to of series and other, element-wise (binary operator ne). |
| 99 | nlargest([n, keep]) | Return the largest n elements. |
| 100 | notna() | Detect existing (non-missing) values. |
| 101 | notnull() | Detect existing (non-missing) values. |
| 102 | nsmallest([n, keep]) | Return the smallest n elements. |
| 103 | nunique([dropna]) | Return number of unique elements in the object. |
| 104 | pad([axis, inplace, limit, downcast]) | Synonym for DataFrame.fillna() with method='ffill'. |
| 105 | pct_change([periods, fill_method, limit, freq]) | Percentage change between the current and a prior element. |
| 106 | pipe(func, *args, **kwargs) | Apply func(self, *args, **kwargs). |
| 107 | plot | alias of pandas.plotting._core.PlotAccessor |
| 108 | pop(item) | Return item and drops from series. |
| 109 | pow(other[, level, fill_value, axis]) | Return Exponential power of series and other, element-wise (binary operator pow). |
| 110 | prod([axis, skipna, level, numeric_only, …]) | Return the product of the values over the requested axis. |
| 111 | product([axis, skipna, level, numeric_only, …]) | Return the product of the values over the requested axis. |
| 112 | quantile([q, interpolation]) | Return value at the given quantile. |
| 113 | radd(other[, level, fill_value, axis]) | Return Addition of series and other, element-wise (binary operator radd). |
| 114 | rank([axis, method, numeric_only, …]) | Compute numerical data ranks (1 through n) along axis. |
| 115 | ravel([order]) | Return the flattened underlying data as an ndarray. |
| 116 | rdiv(other[, level, fill_value, axis]) | Return Floating division of series and other, element-wise (binary operator rtruediv). |
| 117 | rdivmod(other[, level, fill_value, axis]) | Return Integer division and modulo of series and other, element-wise (binary operator rdivmod). |
| 118 | reindex([index]) | Conform Series to new index with optional filling logic. |
| 119 | reindex_like(other[, method, copy, limit, …]) | Return an object with matching indices as other object. |
| 120 | rename([index, axis, copy, inplace, level, …]) | Alter Series index labels or name. |
| 121 | rename_axis([mapper, index, columns, axis, …]) | Set the name of the axis for the index or columns. |
| 122 | reorder_levels(order) | Rearrange index levels using input order. |
| 123 | repeat(repeats[, axis]) | Repeat elements of a Series. |
| 124 | replace([to_replace, value, inplace, limit, …]) | Replace values given in to_replace with value. |
| 125 | resample(rule[, axis, closed, label, …]) | Resample time-series data. |
| 126 | reset_index([level, drop, name, inplace]) | Generate a new DataFrame or Series with the index reset. |
| 127 | rfloordiv(other[, level, fill_value, axis]) | Return Integer division of series and other, element-wise (binary operator rfloordiv). |
| 128 | rmod(other[, level, fill_value, axis]) | Return Modulo of series and other, element-wise (binary operator rmod). |
| 129 | rmul(other[, level, fill_value, axis]) | Return Multiplication of series and other, element-wise (binary operator rmul). |
| 130 | rolling(window[, min_periods, center, …]) | Provide rolling window calculations. |
| 131 | round([decimals]) | Round each value in a Series to the given number of decimals. |
| 132 | rpow(other[, level, fill_value, axis]) | Return Exponential power of series and other, element-wise (binary operator rpow). |
| 133 | rsub(other[, level, fill_value, axis]) | Return Subtraction of series and other, element-wise (binary operator rsub). |
| 134 | rtruediv(other[, level, fill_value, axis]) | Return Floating division of series and other, element-wise (binary operator rtruediv). |
| 135 | sample([n, frac, replace, weights, …]) | Return a random sample of items from an axis of object. |
| 136 | searchsorted(value[, side, sorter]) | Find indices where elements should be inserted to maintain order. |
| 137 | sem([axis, skipna, level, ddof, numeric_only]) | Return unbiased standard error of the mean over requested axis. |
| 138 | set_axis(labels[, axis, inplace]) | Assign desired index to given axis. |
| 139 | set_flags(*[, copy, allows_duplicate_labels]) | Return a new object with updated flags. |
| 140 | shift([periods, freq, axis, fill_value]) | Shift index by desired number of periods with an optional time freq. |
| 141 | skew([axis, skipna, level, numeric_only]) | Return unbiased skew over requested axis. |
| 142 | slice_shift([periods, axis]) | (DEPRECATED) Equivalent to shift without copying data. |
| 143 | sort_index([axis, level, ascending, …]) | Sort Series by index labels. |
| 144 | sort_values([axis, ascending, inplace, …]) | Sort by the values. |
| 145 | sparse | alias of pandas.core.arrays.sparse.accessor.SparseAccessor |
| 146 | squeeze([axis]) | Squeeze 1 dimensional axis objects into scalars. |
| 147 | std([axis, skipna, level, ddof, numeric_only]) | Return sample standard deviation over requested axis. |
| 148 | str | alias of pandas.core.strings.accessor.StringMethods |
| 149 | sub(other[, level, fill_value, axis]) | Return Subtraction of series and other, element-wise (binary operator sub). |
| 150 | subtract(other[, level, fill_value, axis]) | Return Subtraction of series and other, element-wise (binary operator sub). |
| 151 | sum([axis, skipna, level, numeric_only, …]) | Return the sum of the values over the requested axis. |
| 152 | swapaxes(axis1, axis2[, copy]) | Interchange axes and swap values axes appropriately. |
| 153 | swaplevel([i, j, copy]) | Swap levels i and j in a MultiIndex. |
| 154 | tail([n]) | Return the last n rows. |
| 155 | take(indices[, axis, is_copy]) | Return the elements in the given positional indices along an axis. |
| 156 | to_clipboard([excel, sep]) | Copy object to the system clipboard. |
| 157 | to_csv([path_or_buf, sep, na_rep, …]) | Write object to a comma-separated values (csv) file. |
| 158 | to_dict([into]) | Convert Series to {label -> value} dict or dict-like object. |
| 159 | to_excel(excel_writer[, sheet_name, na_rep, …]) | Write object to an Excel sheet. |
| 160 | to_frame([name]) | Convert Series to DataFrame. |
| 161 | to_hdf(path_or_buf, key[, mode, complevel, …]) | Write the contained data to an HDF5 file using HDFStore. |
| 162 | to_json([path_or_buf, orient, date_format, …]) | Convert the object to a JSON string. |
| 163 | to_latex([buf, columns, col_space, header, …]) | Render object to a LaTeX tabular, longtable, or nested table/tabular. |
| 164 | to_list() | Return a list of the values. |
| 165 | to_markdown([buf, mode, index, storage_options]) | Print Series in Markdown-friendly format. |
| 166 | to_numpy([dtype, copy, na_value]) | A NumPy ndarray representing the values in this Series or Index. |
| 167 | to_period([freq, copy]) | Convert Series from DatetimeIndex to PeriodIndex. |
| 168 | to_pickle(path[, compression, protocol, …]) | Pickle (serialize) object to file. |
| 169 | to_sql(name, con[, schema, if_exists, …]) | Write records stored in a DataFrame to a SQL database. |
| 170 | to_string([buf, na_rep, float_format, …]) | Render a string representation of the Series. |
| 171 | to_timestamp([freq, how, copy]) | Cast to DatetimeIndex of Timestamps, at beginning of period. |
| 172 | to_xarray() | Return an xarray object from the pandas object. |
| 173 | tolist() | Return a list of the values. |
| 174 | transform(func[, axis]) | Call func on self producing a Series with transformed values. |
| 175 | transpose(*args, **kwargs) | Return the transpose, which is by definition self. |
| 176 | truediv(other[, level, fill_value, axis]) | Return Floating division of series and other, element-wise (binary operator truediv). |
| 177 | truncate([before, after, axis, copy]) | Truncate a Series or DataFrame before and after some index value. |
| 178 | tshift([periods, freq, axis]) | (DEPRECATED) Shift the time index, using the index’s frequency if available. |
| 179 | tz_convert(tz[, axis, level, copy]) | Convert tz-aware axis to target time zone. |
| 180 | tz_localize(tz[, axis, level, copy, …]) | Localize tz-naive index of a Series or DataFrame to target time zone. |
| 181 | unique() | Return unique values of Series object. |
| 182 | unstack([level, fill_value]) | Unstack, also known as pivot, Series with MultiIndex to produce DataFrame. |
| 183 | update(other) | Modify Series in place using values from passed Series. |
| 184 | value_counts([normalize, sort, ascending, …]) | Return a Series containing counts of unique values. |
| 185 | var([axis, skipna, level, ddof, numeric_only]) | Return unbiased variance over requested axis. |
| 186 | view([dtype]) | Create a new view of the Series. |
| 187 | where(cond[, other, inplace, axis, level, …]) | Replace values where the condition is False. |
| 188 | xs(key[, axis, level, drop_level]) | Return cross-section from the Series/DataFrame. |