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 powerful Python data analysis toolkit, Release 0.13.1 • pd.melt() now accepts the optional parameters var_name and value_name to specify custom column names of the returned DataFrame. • pd.set_option() now max Maximum mode Mode 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

read milliseconds in Excel dates and times with xlrd >= 0.9.3. (GH5945) • pd.stats.moments.rolling_var now uses Welford’s method for increased numerical stability (GH6817) • pd.expanding_apply and pd.rolling_apply 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 powerful Python data analysis toolkit, Release 0.14.0 • pd.melt() now accepts the optional parameters var_name and value_name to specify custom column names of the returned DataFrame. • pd.set_option() now

Minimum max Maximum 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 values rolling_min Minimum rolling_max Maximum rolling_std Unbiased standard deviation rolling_var Unbiased variance rolling_skew Unbiased skewness (3rd moment) rolling_kurt Unbiased kurtosis (4th rolling_median(arg, window[, min_periods, ...]) O(N log(window)) implementation using skip list rolling_var(arg, window[, min_periods, ...]) Unbiased moving variance rolling_std(arg, window[, min_periods,

Minimum max Maximum 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 values rolling_min Minimum rolling_max Maximum rolling_std Unbiased standard deviation rolling_var Unbiased variance rolling_skew Unbiased skewness (3rd moment) rolling_kurt Unbiased kurtosis (4th rolling_median(arg, window[, min_periods, ...]) O(N log(window)) implementation using skip list rolling_var(arg, window[, min_periods, ...]) Unbiased moving variance rolling_std(arg, window[, min_periods,

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 + replace all occurrences of the string ’.’ with NaN. • pd.melt() now accepts the optional parameters var_name and value_name to specify custom column names of the returned DataFrame. • pd.set_option() now Minimum max Maximum 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

rolling_max(), 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() of 1 is backwards-compatible. (GH8279) • Documented the ddof argument to expanding_var(), expanding_std(), rolling_var(), and rolling_std(). These functions’ support of a ddof argument (with a default (GH8080) • Bug in expanding_std() and expanding_var() for a single value producing a confusing error message (GH7900) • Bug in rolling_std() and rolling_var() for a single value producing 0 rather than NaN

rolling_max(), 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() of 1 is backwards-compatible. (GH8279) • Documented the ddof argument to expanding_var(), expanding_std(), rolling_var(), and rolling_std(). These functions’ support of a ddof argument (with a default (GH8080) • Bug in expanding_std() and expanding_var() for a single value producing a confusing error message (GH7900) • Bug in rolling_std() and rolling_var() for a single value producing 0 rather than NaN

median . . . . . . . . . . . . . . . . . . . . . . . . . 1767 34.12.1.5 pandas.core.window.Rolling.var . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1767 xxxix 34.12.1.6 pandas.core.window.Rolling median . . . . . . . . . . . . . . . . . . . . . . . 1771 34.12.2.5 pandas.core.window.Expanding.var . . . . . . . . . . . . . . . . . . . . . . . . . . 1772 34.12.2.6 pandas.core.window.Expanding.std std . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1775 34.12.3.3 pandas.core.window.EWM.var . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1775 34.12.3.4 pandas.core.window.EWM.corr

(GH12004) • read_stata() can read Stata 119 dta files. (GH28250) • Implemented pandas.core.window.Window.var() and pandas.core.window.Window. std() functions (GH26597) • Added encoding argument to DataFrame locales -a encodes the lo- cales list as windows-1252 (GH23638, GH24760, GH27368) • Bug in Series.var() failing to raise TypeError when called with timedelta64[ns] dtype (GH28289) • Bug in DatetimeIndex where specifying axis by name references variable before it is as- signed (GH29142) • Bug in Series.var() not computing the right value with a nullable integer dtype series not passing through ddof argument

Minimum max Maximum 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 values rolling_min Minimum rolling_max Maximum rolling_std Unbiased standard deviation rolling_var Unbiased variance rolling_skew Unbiased skewness (3rd moment) rolling_kurt Unbiased kurtosis (4th rolling_median(arg, window[, min_periods, ...]) O(N log(window)) implementation using skip list rolling_var(arg, window[, min_periods, ...]) Unbiased moving variance rolling_std(arg, window[, min_periods,