files (CSV and delimited), Excel files, databases, and saving / loading data from the ultrafast HDF5 format • Time series-specific functionality: date range generation and frequency conversion, moving window isin function which checks if each value is contained in a passed sequence (GH289) • Added float_format option to Series.to_string • Added skip_footer (GH291) and converters (GH343) options to read_csv show index level names in console output (PR334) • Implemented Panel.take • Added set_eng_float_format for alternate DataFrame floating point string formatting (ENH61) 1.7. v.0.5.0 (October 24, 2011)

files (CSV and delimited), Excel files, databases, and saving / loading data from the ultrafast HDF5 format • Time series-specific functionality: date range generation and frequency conversion, moving window isin function which checks if each value is contained in a passed sequence (GH289) • Added float_format option to Series.to_string 1.3. v.0.6.1 (December 13, 2011) 9 pandas: powerful Python data analysis show index level names in console output (PR334) • Implemented Panel.take • Added set_eng_float_format for alternate DataFrame floating point string formatting (ENH61) • Added convenience set_index function

files (CSV and delimited), Excel files, databases, and saving / loading data from the ultrafast HDF5 format • Time series-specific functionality: date range generation and frequency conversion, moving window isin function which checks if each value is contained in a passed sequence (GH289) • Added float_format option to Series.to_string • Added skip_footer (GH291) and converters (GH343) options to read_csv show index level names in console output (PR334) • Implemented Panel.take • Added set_eng_float_format for alternate DataFrame floating point string formatting (ENH61) • Added convenience set_index function

. . . . . . . . . . . . . . . . . . . . . . . . 8 1.2.1.1 Integration with Apache Parquet file format . . . . . . . . . . . . . . . . . . . . . 8 1.2.1.2 infer_objects type conversion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 844 19.3.1 Providing a Format Argument . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 844 19.3.2 Assembling . . . . . . . . . . . . . . . . . . . . . . . . . 1031 24.1.1.7 Quoting, Compression, and File Format . . . . . . . . . . . . . . . . . . . . . . . 1031 24.1.1.8 Error Handling . . . . . . . . . .

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 384 2.4.18 Stata format . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 384 2.4.19 . . . . . . . . . . . . . . . . . 2674 4.11.1 Storing pandas DataFrame objects in Apache Parquet format . . . . . . . . . . . . . . . . . 2674 4.12 Policies . . . . . . . . . . . . . . . . . . . . . multiple ways. You can melt() your data table from wide to long/tidy form or pivot() from long to wide format. With aggregations built-in, a pivot table is created with a single command. To introduction tutorial

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 401 2.4.18 Stata format . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 401 2.4.19 . . . . . . . . . . . . . . . . . 2753 4.11.1 Storing pandas DataFrame objects in Apache Parquet format . . . . . . . . . . . . . . . . . 2753 4.12 Policies . . . . . . . . . . . . . . . . . . . . . multiple ways. You can melt() your data table from wide to long/tidy form or pivot() from long to wide format. With aggregations built-in, a pivot table is created with a single command. To introduction tutorial

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 401 2.4.18 Stata format . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 401 2.4.19 . . . . . . . . . . . . . . . . . 2753 4.11.1 Storing pandas DataFrame objects in Apache Parquet format . . . . . . . . . . . . . . . . . 2753 4.12 Policies . . . . . . . . . . . . . . . . . . . . . multiple ways. You can melt() your data table from wide to long/tidy form or pivot() from long to wide format. With aggregations built-in, a pivot table is created with a single command. To introduction tutorial

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 179 3.5 Converting to and from period format . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 180 3.6 Treatment of missing (Experimental) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 730 23.11 Stata Format . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 731 files (CSV and delimited), Excel files, databases, and saving / loading data from the ultrafast HDF5 format • Time series-specific functionality: date range generation and frequency conversion, moving window

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 173 3.5 Converting to and from period format . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 174 3.6 Treatment of missing (Experimental) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 716 23.11 STATA Format . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 717 23 files (CSV and delimited), Excel files, databases, and saving / loading data from the ultrafast HDF5 format • Time series-specific functionality: date range generation and frequency conversion, moving window

. . . . . . . . . . . . . . . . . . . . . . . . . . 997 24.1.1.7 Quoting, Compression, and File Format . . . . . . . . . . . . . . . . . . . . . . . 997 24.1.1.8 Error Handling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1010 24.1.9.3 Inferring Datetime Format . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1010 24.1.9.4 International Date Formats . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1023 24.1.26.1 Writing to CSV format . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1023 24.1.26.2 Writing a formatted