Representations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 307 15.10 Time Zone Handling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 309 15.11 many other 3rd party libraries. Here are just a few of the things that pandas does well: • Easy handling of missing data (represented as NaN) in floating point as well as non-floating point data • Size [14]: df.iloc[mask.values] a A 0 C 2 E 4 df.iloc[mask] will raise a ValueError • The raise_on_error argument to plotting functions is removed. Instead, plotting functions raise a TypeError when the

will now be consistent with extension types . . . . . . . . . . . . . . . . 25 1.3.2.5 S3 File Handling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26 1.3.2.6 Partial String read_csv exceptions . . . . . . . . . . . . . . . . . . . . . . . . . . 104 1.7.3.5 to_datetime error changes . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105 1.7.3.6 Other API changes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 219 1.16.1.5 Timezone handling improvements . . . . . . . . . . . . . . . . . . . . . . . . . . 221 1.16.1.6 Rolling/Expanding

will now be consistent with extension types . . . . . . . . . . . . . . . . 23 1.2.2.5 S3 File Handling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24 1.2.2.6 Partial String read_csv exceptions . . . . . . . . . . . . . . . . . . . . . . . . . . 102 1.6.3.5 to_datetime error changes . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103 1.6.3.6 Other API changes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 217 1.15.1.5 Timezone handling improvements . . . . . . . . . . . . . . . . . . . . . . . . . . 220 1.15.1.6 Rolling/Expanding

Representations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 400 16.10 Time Zone Handling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 401 16.11 many other 3rd party libraries. Here are just a few of the things that pandas does well: • Easy handling of missing data (represented as NaN) in floating point as well as non-floating point data • Size handle is_open; a closed store will now report ‘CLOSED’ when viewing the store (rather than raising an error) (GH4409) • a close of a HDFStore now will close that instance of the HDFStore but will only close

PeriodIndex resampling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 1.2.2.8 Improved error handling during item assignment in pd.eval . . . . . . . . . . . . . 21 1.2.2.9 Dtype Conversions . will now be consistent with extension types . . . . . . . . . . . . . . . . 54 1.5.2.5 S3 File Handling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55 1.5.2.6 Partial String read_csv exceptions . . . . . . . . . . . . . . . . . . . . . . . . . . 133 1.9.3.5 to_datetime error changes . . . . . . . . . . . . . . . . . . . . . . . . . . . . 134 1.9.3.6 Other API changes .

read_csv exceptions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56 to_datetime error changes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57 Other API changes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 171 Timezone handling improvements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 174 Rolling/Expanding “nuisance” columns . . . . . . . . . . . . . . . . . . . . . . . . . . 669 17.9.2 NA and NaT group handling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 670 17.9.3 Grouping with ordered

read_csv exceptions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55 to_datetime error changes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56 Other API changes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 170 Timezone handling improvements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 173 Rolling/Expanding “nuisance” columns . . . . . . . . . . . . . . . . . . . . . . . . . . 667 17.9.2 NA and NaT group handling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 668 17.9.3 Grouping with ordered

spans . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 626 20.12 Time Zone Handling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 627 21 Time many other 3rd party libraries. Here are just a few of the things that pandas does well: • Easy handling of missing data (represented as NaN) in floating point as well as non-floating point data • Size incompatible API changes – Changes to sorting API – Changes to to_datetime and to_timedelta * Error handling * Consistent Parsing – Changes to Index Comparisons – Changes to Boolean Comparisons vs. None

Representations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 441 16.10 Time Zone Handling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 442 16.11 many other 3rd party libraries. Here are just a few of the things that pandas does well: • Easy handling of missing data (represented as NaN) in floating point as well as non-floating point data • Size The top-level pandas.eval() function does not allow you use the ’@’ prefix and provides you with an error message telling you so. – NameResolutionError was removed because it isn’t necessary anymore. •

spans . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 532 19.11 Time Zone Handling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 532 20 Time many other 3rd party libraries. Here are just a few of the things that pandas does well: • Easy handling of missing data (represented as NaN) in floating point as well as non-floating point data • Size dates are available from Yahoo and when it receives no data from Yahoo (GH8761), (GH8783). • Unclear error message in csv parsing when passing dtype and names and the parsed data is a different data type (GH8833)