elle
(Elle)
#1
I/O with pandas
One of the major strengths of the pandas library is that it can read and write different data
formats natively, including among others:
CSV (comma-separated value)
SQL (Structured Query Language)
XLS/XSLX (Microsoft Excel files)
JSON (JavaScript Object Notation)
HTML (HyperText Markup Language)
Table 7-1 lists all the supported formats and the corresponding import and export
functions/methods of pandas. The parameters that the import functions take are listed and
described in Table 6-6 (depending on the functions, some other conventions might apply).
Table 7-1. Parameters of DataFrame function
Format Input Output Remark
CSV
read_csv
to_csv
Text file
XLS/XLSX
read_excel
to_excel
Spreadsheet
HDF
read_hdf
to_hdf
HDF5 database
SQL
read_sql
to_sql
SQL table
JSON
read_json
to_json
JavaScript Object Notation
MSGPACK
read_msgpack
to_msgpack
Portable binary format
HTML
read_html
to_html
HTML code
GBQ
read_gbq
to_gbq
Google Big Query format
DTA
read_stata
to_stata
Formats 104, 105, 108, 113-115, 117
Any
read_clipboard
to_clipboard
E.g., from HTML page
Any
read_pickle
to_pickle
(Structured) Python object
