. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1213 33.4 String Processing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1213 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1219 33.7.3 By Group Processing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1220 33.8 Other Considerations (GH11256) • Bug in pd.read_csv() in which the dialect parameter was not being verified before processing (GH14898) • Bug in pd.read_csv() in which missing data was being improperly handled with usecols

Out[70]: 3 4 1 3 5 2 4 1 dtype: int64 String Methods Series is equipped with a set of string processing methods in the str attribute that make it easy to operate on each element of the array, as in the toolkit, Release 0.25.3 3.3.10 Vectorized string methods Series is equipped with a set of string processing methods that make it easy to operate on each element of the array. Perhaps most importantly, these Sat Dinner 1 145 6.35 1.50 Female No Thur Lunch 2 135 6.51 1.25 Female No Thur Lunch 2 String processing Length SAS determines the length of a character string with the LENGTHN and LENGTHC functions

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1181 33.6.3 By Group Processing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1181 33.7 Other Considerations (GH11256) • Bug in pd.read_csv() in which the dialect parameter was not being verified before processing (GH14898) • Bug in pd.read_csv() in which missing data was being improperly handled with usecols Bug in pd.read_csv() which may cause a segfault or corruption when iterating in large chunks over a stream/file under rare circumstances (GH13703) • Bug in pd.read_csv() which caused errors to be raised

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1179 xxiii 33.6.3 By Group Processing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1179 33.7 Other Considerations (GH11256) • Bug in pd.read_csv() in which the dialect parameter was not being verified before processing (GH14898) • Bug in pd.read_csv() in which missing data was being improperly handled with usecols Bug in pd.read_csv() which may cause a segfault or corruption when iterating in large chunks over a stream/file under rare circumstances (GH13703) • Bug in pd.read_csv() which caused errors to be raised

arising from a converter function as NA if passed in the na_values argument. It’s better to do post-processing using the replace function instead. • Calling fillna on Series or DataFrame with no arguments Finance. 1.6.1 New features • Add encode and decode for unicode handling to vectorized string processing methods in Series.str (GH1706) • Add DataFrame.to_latex method (GH1735) • Add convenient expanding features include notably NA friendly string processing functionality and a series of new plot types and options. 1.7.1 New features • Add vectorized string processing methods accessible via Series.str (GH620)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1087 34.6.3 By Group Processing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1087 34.7 Other Considerations Bug in pd.read_csv() which may cause a segfault or corruption when iterating in large chunks over a stream/file under rare circumstances (GH13703) • Bug in pd.read_csv() which caused errors to be raised resample(..).fillna(..) when passing a non-string (GH12952) • Bug fixes in various encoding and header processing issues in pd.read_sas() (GH12659, GH12654, GH12647, GH12809) • Bug in pd.crosstab() where would

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1089 34.6.3 By Group Processing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1089 34.7 Other Considerations Bug in pd.read_csv() which may cause a segfault or corruption when iterating in large chunks over a stream/file under rare circumstances (GH13703) • Bug in pd.read_csv() which caused errors to be raised resample(..).fillna(..) when passing a non-string (GH12952) • Bug fixes in various encoding and header processing issues in pd.read_sas() (GH12659, GH12654, GH12647, GH12809) • Bug in pd.crosstab() where would

2 2 6 1 5 1 4 1 1 1 dtype: int64 String Methods Series is equipped with a set of string processing methods in the str attribute that make it easy to operate on each element of the array, as in the a non-datetime-like values. Vectorized string methods Series is equipped with a set of string processing methods that make it easy to operate on each element of the array. Perhaps most importantly, these Sat Dinner 1 145 6.35 1.50 Female No Thur Lunch 2 135 6.51 1.25 Female No Thur Lunch 2 String processing Length SAS determines the length of a character string with the LENGTHN and LENGTHC functions

Out[70]: 2 5 3 3 6 1 0 1 dtype: int64 String Methods Series is equipped with a set of string processing methods in the str attribute that make it easy to operate on each element of the array, as in the a non-datetime-like values. Vectorized string methods Series is equipped with a set of string processing methods that make it easy to operate on each element of the array. Perhaps most importantly, these Sat Dinner 1 145 6.35 1.50 Female No Thur Lunch 2 135 6.51 1.25 Female No Thur Lunch 2 String processing Length SAS determines the length of a character string with the LENGTHN and LENGTHC functions

Sat Dinner 1 145 6.35 1.50 Female No Thur Lunch 2 135 6.51 1.25 Female No Thur Lunch 2 String processing Length SAS determines the length of a character string with the LENGTHN and LENGTHC functions data analysis toolkit, Release 1.1.1 By group processing In addition to aggregation, pandas groupby can be used to replicate most other by group processing from SAS. For example, this DATA step reads the your machine’s memory, but also that the operations on that data may be faster. If out of core processing is needed, one possibility is the dask.dataframe library (currently in development) which provides