abs Absolute Value prod Product of values std Unbiased standard deviation var Unbiased variance skew Unbiased skewness (3rd moment) kurt Unbiased kurtosis (4th moment) quantile Sample quantile (value Among these are count, sum, mean, median, correlation, variance, covariance, standard deviation, skew- ness, and kurtosis. All of these methods are in the pandas namespace, but otherwise they can be found rolling_max Maximum rolling_std Unbiased standard deviation rolling_var Unbiased variance rolling_skew Unbiased skewness (3rd moment) rolling_kurt Unbiased kurtosis (4th moment) rolling_quantile Sample

abs Absolute Value prod Product of values std Unbiased standard deviation var Unbiased variance skew Unbiased skewness (3rd moment) kurt Unbiased kurtosis (4th moment) quantile Sample quantile (value Among these are count, sum, mean, median, correlation, variance, covariance, standard deviation, skew- ness, and kurtosis. All of these methods are in the pandas namespace, but otherwise they can be found rolling_max Maximum rolling_std Unbiased standard deviation rolling_var Unbiased variance rolling_skew Unbiased skewness (3rd moment) rolling_kurt Unbiased kurtosis (4th moment) rolling_quantile Sample

performing these operations on, for example, a DataFrame of slice objects: – sum, prod, mean, std, var, skew, kurt, corr, and cov 36 Chapter 1. What’s New pandas: powerful Python data analysis toolkit, Release abs Absolute Value prod Product of values std Unbiased standard deviation var Unbiased variance skew Unbiased skewness (3rd moment) kurt Unbiased kurtosis (4th moment) quantile Sample quantile (value Among these are count, sum, mean, median, correlation, variance, covariance, standard deviation, skew- ness, and kurtosis. All of these methods are in the pandas namespace, but otherwise they can be found

abs Absolute Value prod Product of values std Unbiased standard deviation var Unbiased variance skew Unbiased skewness (3rd moment) kurt Unbiased kurtosis (4th moment) quantile Sample quantile (value Among these are count, sum, mean, median, correlation, variance, covariance, standard deviation, skew- ness, and kurtosis. All of these methods are in the pandas namespace, but otherwise they can be found rolling_max Maximum rolling_std Unbiased standard deviation rolling_var Unbiased variance rolling_skew Unbiased skewness (3rd moment) rolling_kurt Unbiased kurtosis (4th moment) rolling_quantile Sample

performing these operations on, for example, a DataFrame of slice objects: – sum, prod, mean, std, var, skew, kurt, corr, and cov 1.4. v0.12.0 (July 24, 2013) 63 pandas: powerful Python data analysis toolkit abs Absolute Value prod Product of values std Unbiased standard deviation var Unbiased variance skew Unbiased skewness (3rd moment) kurt Unbiased kurtosis (4th moment) quantile Sample quantile (value Among these are count, sum, mean, median, correlation, variance, covariance, standard deviation, skew- ness, and kurtosis. All of these methods are in the pandas namespace, but otherwise they can be found

rolling_min(), rolling_sum(), rolling_mean(), rolling_median(), rolling_std(), rolling_var(), rolling_skew(), rolling_kurt(), rolling_quantile(), rolling_cov(), rolling_corr(), rolling_corr_pairwise(), rolling_window() performing these operations on, for example, a DataFrame of slice objects: – sum, prod, mean, std, var, skew, kurt, corr, and cov 1.8. v0.12.0 (July 24, 2013) 107 pandas: powerful Python data analysis toolkit std Unbiased standard deviation var Unbiased variance sem Unbiased standard error of the mean skew Unbiased skewness (3rd moment) kurt Unbiased kurtosis (4th moment) quantile Sample quantile (value

rolling_min(), rolling_sum(), rolling_mean(), rolling_median(), rolling_std(), rolling_var(), rolling_skew(), rolling_kurt(), rolling_quantile(), rolling_cov(), rolling_corr(), rolling_corr_pairwise(), rolling_window() performing these operations on, for example, a DataFrame of slice objects: – sum, prod, mean, std, var, skew, kurt, corr, and cov 1.7. v0.12.0 (July 24, 2013) 101 pandas: powerful Python data analysis toolkit std Unbiased standard deviation var Unbiased variance sem Unbiased standard error of the mean skew Unbiased skewness (3rd moment) kurt Unbiased kurtosis (4th moment) quantile Sample quantile (value

rolling_min(), rolling_sum(), rolling_mean(), rolling_median(), rolling_std(), rolling_var(), rolling_skew(), rolling_kurt(), rolling_quantile(), rolling_cov(), rolling_corr(), rolling_corr_pairwise(), rolling_window() performing these operations on, for example, a DataFrame of slice objects: – sum, prod, mean, std, var, skew, kurt, corr, and cov 162 Chapter 1. What’s New pandas: powerful Python data analysis toolkit, Release std Unbiased standard deviation var Unbiased variance sem Unbiased standard error of the mean skew Unbiased skewness (3rd moment) kurt Unbiased kurtosis (4th moment) quantile Sample quantile (value

performing these operations on, for example, a DataFrame of slice objects: – sum, prod, mean, std, var, skew, kurt, corr, and cov • read_html now defaults to None when reading, and falls back on bs4 + html5lib abs Absolute Value prod Product of values std Unbiased standard deviation var Unbiased variance skew Unbiased skewness (3rd moment) kurt Unbiased kurtosis (4th moment) quantile Sample quantile (value Among these are count, sum, mean, median, correlation, variance, covariance, standard deviation, skew- ness, and kurtosis. All of these methods are in the pandas namespace, but otherwise they can be found

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1708 pandas.core.window.Rolling.skew . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1708 pandas.core.window.Rolling.kurt cov . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1712 pandas.core.window.Expanding.skew . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1713 pandas.core.window.Expanding.kurt size . . . . . . . . . . . . . . . . . . . . . . . . . . 1735 pandas.core.groupby.DataFrameGroupBy.skew . . . . . . . . . . . . . . . . . . . . . . . . . 1735 pandas.core.groupby.DataFrameGroupBy.take