boolean indexer. (Their distinction is strictness: match relies on re.match while contains relies on re.search.) In this release, the deprecated behavior is the default, but the new behavior is available through between match and contains is strictness: match relies on strict re.match, while contains relies on re.search. 9.9. Vectorized string methods 207 pandas: powerful Python data analysis toolkit, Release 0.13 out pandas/core/config.py for more info. All of the functions above accept a regexp pattern (re.search style) as an argument, and so passing in a substring will work - as long as it is unambiguous :

boolean indexer. (Their distinction is strictness: match relies on re.match while contains relies on re.search.) In this release, the deprecated behavior is the default, but the new behavior is available through between match and contains is strictness: match relies on strict re.match, while contains relies on re.search. Warning: In previous versions, match was for extracting groups, returning a not-so-convenient Series out pandas/core/config.py for more info. All of the functions above accept a regexp pattern (re.search style) as an argument, and so passing in a substring will work - as long as it is unambiguous :

boolean indexer. (Their distinction is strictness: match relies on re.match while contains relies on re.search.) In this release, the deprecated behavior is the default, but the new behavior is available through between match and contains is strictness: match relies on strict re.match, while contains relies on re.search. Warning: In previous versions, match was for extracting groups, returning a not-so-convenient Series out pandas/core/config.py for more info. All of the functions above accept a regexp pattern (re.search style) as an argument, and so passing in a substring will work - as long as it is unambiguous :

boolean indexer. (Their distinction is strictness: match relies on re.match while contains relies on re.search.) In this release, the deprecated behavior is the default, but the new behavior is available through between match and contains is strictness: match relies on strict re.match, while contains relies on re.search. Warning: In previous versions, match was for extracting groups, returning a not-so-convenient Series out pandas/core/config.py for more info. All of the functions above accept a regexp pattern (re.search style) as an argument, and so passing in a substring will work - as long as it is unambiguous :

boolean indexer. (Their distinction is strictness: match relies on re.match while contains relies on re.search.) In this release, the deprecated behavior is the default, but the new behavior is available through between match and contains is strictness: match relies on strict re.match, while contains relies on re.search. 392 Chapter 11. Working with Text Data pandas: powerful Python data analysis toolkit, Release out pandas/core/config.py for more info. All of the functions above accept a regexp pattern (re.search style) as an argument, and so passing in a substring will work - as long as it is unambiguous :

boolean indexer. (Their distinction is strictness: match relies on re.match while contains relies on re.search.) In this release, the deprecated behavior is the default, but the new behavior is available through between match and contains is strictness: match relies on strict re.match, while contains relies on re.search. Methods like match, contains, startswith, and endswith take an extra na argument so missing values string match() Call re.match on each element, returning matched groups as list extract() Call re.search on each element, returning DataFrame with one row for each element and one column for each regex

boolean indexer. (Their distinction is strictness: match relies on re.match while contains relies on re.search.) In this release, the deprecated behavior is the default, but the new behavior is available through your branch. Expand the following line in the build log: ci/print_skipped.py /tmp/nosetests.xml . Search for the term test_gbq and confirm that gbq integration tests are not skipped. Running the vbench between match and contains is strictness: match relies on strict re.match, while contains relies on re.search. Warning: In previous versions, match was for extracting groups, returning a not-so-convenient Series

boolean indexer. (Their distinction is strictness: match relies on re.match while contains relies on re.search.) In this release, the deprecated behavior is the default, but the new behavior is available through your branch. Expand the following line in the build log: ci/print_skipped.py /tmp/nosetests.xml . Search for the term test_gbq and confirm that gbq integration tests are not skipped. Running the vbench between match and contains is strictness: match relies on strict re.match, while contains relies on re.search. Warning: In previous versions, match was for extracting groups, returning a not-so-convenient Series

boolean indexer. (Their distinction is strictness: match relies on re.match while contains relies on re.search.) In this release, the deprecated behavior is the default, but the new behavior is available through between match and contains is strictness: match relies on strict re.match, while contains relies on re.search. Methods like match, contains, startswith, and endswith take an extra na argument so missing values string match() Call re.match on each element, returning matched groups as list extract() Call re.search on each element, returning DataFrame with one row for each element and one column for each regex

when supplied a scalar value to search for, now returns a scalar instead of an array (GH23801). • Categorical.searchsorted(), when supplied a scalar value to search for, now returns a scalar instead 298656 2000-01-08 -0.618845 1.122438 start and stop parameters can be specified to limit the total search space. These are in terms of the total number of rows in a table. # this is effectively what the 282700 1.220322 C -0.813404 -1.001273 D 1.252998 0.162172 [20 rows x 2 columns] # limiting the search In [427]: store.select('wp', "major_axis>20000102 & minor_axis=['A', 'B']", .....: start=0, stop=10)