on dtype . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 384 11 Working with Text Data 387 11.1 Splitting and Replacing Strings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 740 24 IO Tools (Text, CSV, HDF5, ...) 755 24.1 CSV & Text files . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 889 28.7 Parsing Dates from Text Files . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 889 28.8 Differences

Changes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 280 1.20.3 Text Parsing API Changes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 282 1.20 Linux distribution’s package manager. . . . . . . . . . . . . . . . . . . 400 2.2.5 Installing from source . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 401 2.2.6 Running the on dtype . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 581 10 Working with Text Data 585 10.1 Splitting and Replacing Strings . . . . . . . . . . . . . . . . . . . . . . . . .

Version | Zipped HTML Useful links: Binary Installers | Source Repository | Issues & Ideas | Q&A Support | Mailing List pandas is an open source, BSD-licensed library providing high-performance, easy-to-use dtype-specific operations like DataFrame.select_dtypes(). There isn’t a clear way to select just text while excluding non-text, but still object-dtype columns. 3. When reading code, the contents of an object dtype 3, dtype: Int64 We recommend explicitly using the string data type when working with strings. See Text Data Types for more. 1.3.3 Boolean data type with missing values support We’ve added BooleanDtype

. . . . . . . . . . . 227 2.4 IO tools (text, CSV, HDF5, ...) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 230 2.4.1 CSV & text files . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 497 2.9 Working with text data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 499 2.9.1 Text data types . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1880 3.5.10 Text data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1882

. . . . . . . . . . . 227 2.4 IO tools (text, CSV, HDF5, ...) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 230 2.4.1 CSV & text files . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 497 2.9 Working with text data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 499 2.9.1 Text data types . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1880 3.5.10 Text data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1882

Version | Zipped HTML Useful links: Binary Installers | Source Repository | Issues & Ideas | Q&A Support | Mailing List pandas is an open source, BSD-licensed library providing high-performance, easy-to-use In [10]: data = [{ ....: 'CreatedBy': {'Name': 'User001'}, ....: 'Lookup': {'TextField': 'Some text', (continues on next page) 6 Chapter 1. What’s new in 0.25.0 (July 18, 2019) pandas: powerful Python json_normalize(data, max_level=1) Out[11]: CreatedBy.Name Lookup.TextField Lookup.UserField Image.a 0 User001 Some text {'Id': 'ID001', 'Name': 'Name001'} b [1 rows x 4 columns] 1.1.6 Series.explode to split list-like

Version | Zipped HTML Useful links: Binary Installers | Source Repository | Issues & Ideas | Q&A Support | Mailing List pandas is an open source, BSD-licensed library providing high-performance, easy-to-use In [10]: data = [{ ....: 'CreatedBy': {'Name': 'User001'}, ....: 'Lookup': {'TextField': 'Some text', ....: 'UserField': {'Id': 'ID001', 'Name': 'Name001'}}, (continues on next page) 6 Chapter 1 json_normalize(data, max_level=1) Out[11]: CreatedBy.Name Lookup.TextField Lookup.UserField Image.a 0 User001 Some text {'Id': 'ID001', 'Name': 'Name001'} b [1 rows x 4 columns] 1.1.6 Series.explode to split list-like

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66 2.6 Installing from source . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67 2.7 Running . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 354 18 IO Tools (Text, CSV, HDF5, ...) 357 18.1 CSV & Text files . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 426 21.6 Parsing Dates from Text Files . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 426 21.7 Differences

. . 222 2 User Guide 225 2.1 IO tools (text, CSV, HDF5, ...) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 225 2.1.1 CSV & text files . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 489 2.6 Working with text data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 491 2.6.1 Text Data Types . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1804 3.5.10 Text data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1806

. . 222 2 User Guide 225 2.1 IO tools (text, CSV, HDF5, ...) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 225 2.1.1 CSV & text files . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 488 2.6 Working with text data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 490 2.6.1 Text Data Types . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1807 3.5.10 Text data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1809