Input/output

Pickling

read_pickle(filepath_or_buffer[, ...])	Load pickled pandas object (or any object) from file.
DataFrame.to_pickle(path[, compression, ...])	Pickle (serialize) object to file.

Flat 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.
DataFrame.to_csv([path_or_buf, sep, na_rep, ...])	Write object to a comma-separated values (csv) file.
read_fwf(filepath_or_buffer[, colspecs, ...])	Read a table of fixed-width formatted lines into DataFrame.

Clipboard

read_clipboard([sep])	Read text from clipboard and pass to read_csv.
DataFrame.to_clipboard([excel, sep])	Copy object to the system clipboard.

Excel

read_excel(io[, sheet_name, header, names, ...])	Read an Excel file into a pandas DataFrame.
DataFrame.to_excel(excel_writer[, ...])	Write object to an Excel sheet.
ExcelFile.parse([sheet_name, header, names, ...])	Parse specified sheet(s) into a DataFrame.

Styler.to_excel(excel_writer[, sheet_name, ...])

Write Styler to an Excel sheet.

ExcelWriter(path[, engine, date_format, ...])

Class for writing DataFrame objects into excel sheets.

JSON

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.
DataFrame.to_json([path_or_buf, orient, ...])	Convert the object to a JSON string.

build_table_schema(data[, index, ...])

Create a Table schema from data.

HTML

read_html(io[, match, flavor, header, ...])	Read HTML tables into a list of DataFrame objects.
DataFrame.to_html([buf, columns, col_space, ...])	Render a DataFrame as an HTML table.

Styler.to_html([buf, table_uuid, ...])

Write Styler to a file, buffer or string in HTML-CSS format.

XML

read_xml(path_or_buffer[, xpath, ...])	Read XML document into a DataFrame object.
DataFrame.to_xml([path_or_buffer, index, ...])	Render a DataFrame to an XML document.

Latex

DataFrame.to_latex([buf, columns, ...])

Render object to a LaTeX tabular, longtable, or nested table.

Styler.to_latex([buf, column_format, ...])

Write Styler to a file, buffer or string in LaTeX format.

HDFStore: PyTables (HDF5)

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.

Warning

One can store a subclass of DataFrame or Series to HDF5, but the type of the subclass is lost upon storing.

Feather

read_feather(path[, columns, use_threads, ...])	Load a feather-format object from the file path.
DataFrame.to_feather(path, **kwargs)	Write a DataFrame to the binary Feather format.

Parquet

read_parquet(path[, engine, columns, ...])	Load a parquet object from the file path, returning a DataFrame.
DataFrame.to_parquet([path, engine, ...])	Write a DataFrame to the binary parquet format.

ORC

read_orc(path[, columns])

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

SAS

read_sas(filepath_or_buffer[, format, ...])

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

SPSS

read_spss(path[, usecols, convert_categoricals])

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

SQL

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.
DataFrame.to_sql(name, con[, schema, ...])	Write records stored in a DataFrame to a SQL database.

Google BigQuery

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

Load data from Google BigQuery.

STATA

read_stata(filepath_or_buffer[, ...])	Read Stata file into DataFrame.
DataFrame.to_stata(path[, convert_dates, ...])	Export DataFrame object to Stata dta format.

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()	Export DataFrame object to Stata dta format.

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