classmethod DataFrame.from_csv(path, header=0, sep=', ', index_col=0, parse_dates=True, encoding=None, tupleize_cols=False, infer_datetime_format=False) [source] Read CSV file (DISCOURAGED, please use pandas.read_csv() instead). It is preferable to use the more powerful pandas.read_csv() for most general purposes, but from_csv makes for an easy roundtrip to and from a file (the exact counterpart of to_csv), especially with a DataFrame of time series data. This method only differs from the p

DataFrame.floordiv(other, axis='columns', level=None, fill_value=None) [source] Integer division of dataframe and other, element-wise (binary operator floordiv). Equivalent to dataframe // other, but with support to substitute a fill_value for missing data in one of the inputs. Parameters: other : Series, DataFrame, or constant axis : {0, 1, ?index?, ?columns?} For Series input, axis to match Series index on fill_value : None or float value, default None Fill missing (NaN) values with t

DataFrame.first_valid_index() [source] Return label for first non-NA/null value

DataFrame.first(offset) [source] Convenience method for subsetting initial periods of time series data based on a date offset. Parameters: offset : string, DateOffset, dateutil.relativedelta Returns: subset : type of caller Examples ts.first(?10D?) -> First 10 days

DataFrame.filter(items=None, like=None, regex=None, axis=None) [source] Subset rows or columns of dataframe according to labels in the specified index. Note that this routine does not filter a dataframe on its contents. The filter is applied to the labels of the index. Parameters: items : list-like List of info axis to restrict to (must not all be present) like : string Keep info axis where ?arg in col == True? regex : string (regular expression) Keep info axis with re.search(regex, c

DataFrame.fillna(value=None, method=None, axis=None, inplace=False, limit=None, downcast=None, **kwargs) [source] Fill NA/NaN values using the specified method Parameters: value : scalar, dict, Series, or DataFrame Value to use to fill holes (e.g. 0), alternately a dict/Series/DataFrame of values specifying which value to use for each index (for a Series) or column (for a DataFrame). (values not in the dict/Series/DataFrame will not be filled). This value cannot be a list. method : {?bac

DataFrame.ffill(axis=None, inplace=False, limit=None, downcast=None) [source] Synonym for NDFrame.fillna(method=?ffill?)

DataFrame.expanding(min_periods=1, freq=None, center=False, axis=0) [source] Provides expanding transformations. New in version 0.18.0. Parameters: min_periods : int, default None Minimum number of observations in window required to have a value (otherwise result is NA). freq : string or DateOffset object, optional (default None) (DEPRECATED) Frequency to conform the data to before computing the statistic. Specified as a frequency string or DateOffset object. center : boolean, defaul

DataFrame.ewm(com=None, span=None, halflife=None, alpha=None, min_periods=0, freq=None, adjust=True, ignore_na=False, axis=0) [source] Provides exponential weighted functions New in version 0.18.0. Parameters: com : float, optional Specify decay in terms of center of mass, \alpha = 1 / (1 + com),\text{ for } com \geq 0 span : float, optional Specify decay in terms of span, \alpha = 2 / (span + 1),\text{ for } span \geq 1 halflife : float, optional Specify decay in terms of half-life

DataFrame.eval(expr, inplace=None, **kwargs) [source] Evaluate an expression in the context of the calling DataFrame instance. Parameters: expr : string The expression string to evaluate. inplace : bool If the expression contains an assignment, whether to return a new DataFrame or mutate the existing. WARNING: inplace=None currently falls back to to True, but in a future version, will default to False. Use inplace=True explicitly rather than relying on the default. New in version 0.18.