Input/output¶

Pickling¶

read_pickle(filepath_or_buffer[, …])

Load pickled pandas object (or any object) from file.

`read_table`(filepath_or_buffer[, sep, …])	Read general delimited file into DataFrame.
`read_csv`(filepath_or_buffer[, sep, …])	Read a comma-separated values (csv) file into DataFrame.
`read_fwf`(filepath_or_buffer[, colspecs, …])	Read a table of fixed-width formatted lines into DataFrame.

Read text from clipboard and pass to read_csv.

`read_excel`(io[, sheet_name, header, names, …])	Read an Excel file into a pandas DataFrame.
`ExcelFile.parse`([sheet_name, header, names, …])	Parse specified sheet(s) into a DataFrame.

ExcelWriter(path[, engine])

Class for writing DataFrame objects into excel sheets.

`read_json`([path_or_buf, orient, typ, dtype, …])	Convert a JSON string to pandas object.
`json_normalize`(data[, record_path, meta, …])	Normalize semi-structured JSON data into a flat table.

Create a Table schema from data.

read_html(io[, match, flavor, header, …])

Read HTML tables into a list of DataFrame objects.

`read_hdf`(path_or_buf[, key, mode, errors, …])	Read from the store, close it if we opened it.
`HDFStore.put`(key, value[, format, index, …])	Store object in HDFStore.
`HDFStore.append`(key, value[, format, axes, …])	Append to Table in file.
`HDFStore.get`(key)	Retrieve pandas object stored in file.
`HDFStore.select`(key[, where, start, stop, …])	Retrieve pandas object stored in file, optionally based on where criteria.
`HDFStore.info`()	Print detailed information on the store.
`HDFStore.keys`([include])	Return a list of keys corresponding to objects stored in HDFStore.
`HDFStore.groups`()	Return a list of all the top-level nodes.
`HDFStore.walk`([where])	Walk the pytables group hierarchy for pandas objects.

read_feather(path[, columns, use_threads, …])

Load a feather-format object from the file path.

read_parquet(path[, engine, columns, …])

Load a parquet object from the file path, returning a DataFrame.

read_orc(path[, columns])

Load an ORC object from the file path, returning a DataFrame.

read_sas(filepath_or_buffer[, format, …])

Read SAS files stored as either XPORT or SAS7BDAT format files.

read_spss(path[, usecols, convert_categoricals])

Load an SPSS file from the file path, returning a DataFrame.

`read_sql_table`(table_name, con[, schema, …])	Read SQL database table into a DataFrame.
`read_sql_query`(sql, con[, index_col, …])	Read SQL query into a DataFrame.
`read_sql`(sql, con[, index_col, …])	Read SQL query or database table into a DataFrame.

read_gbq(query[, project_id, index_col, …])

Load data from Google BigQuery.

read_stata(filepath_or_buffer[, …])

Read Stata file into DataFrame.

`StataReader.data_label`	Return data label of Stata file.
`StataReader.value_labels`()	Return a dict, associating each variable name a dict, associating each value its corresponding label.
`StataReader.variable_labels`()	Return variable labels as a dict, associating each variable name with corresponding label.
`StataWriter.write_file`()

API reference pandas.read_pickle