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Input/Output¶

Data Generator¶

range(start[, end, step, num_partitions])

Create a DataFrame with some range of numbers.

Spark Metastore Table¶

`read_table`(name[, index_col])	Read a Spark table and return a DataFrame.
`DataFrame.to_table`(name[, format, mode, …])	Write the DataFrame into a Spark table.

Delta Lake¶

`read_delta`(path[, version, timestamp, index_col])	Read a Delta Lake table on some file system and return a DataFrame.
`DataFrame.to_delta`(path[, mode, …])	Write the DataFrame out as a Delta Lake table.

Parquet¶

`read_parquet`(path[, columns, index_col, …])	Load a parquet object from the file path, returning a DataFrame.
`DataFrame.to_parquet`(path[, mode, …])	Write the DataFrame out as a Parquet file or directory.

ORC¶

`read_orc`(path[, columns, index_col])	Load an ORC object from the file path, returning a DataFrame.
`DataFrame.to_orc`(path[, mode, …])	Write the DataFrame out as a ORC file or directory.

Generic Spark I/O¶

`read_spark_io`([path, format, schema, index_col])	Load a DataFrame from a Spark data source.
`DataFrame.to_spark_io`([path, format, mode, …])	Write the DataFrame out to a Spark data source.

Flat File / CSV¶

`read_csv`(path[, sep, header, names, …])	Read CSV (comma-separated) file into DataFrame or Series.
`DataFrame.to_csv`([path, sep, na_rep, …])	Write object to a comma-separated values (csv) file.

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-on-Spark DataFrame or Series.
`DataFrame.to_excel`(excel_writer[, …])	Write object to an Excel sheet.

JSON¶

`read_json`(path[, lines, index_col])	Convert a JSON string to DataFrame.
`DataFrame.to_json`([path, compression, …])	Convert the object to a JSON string.

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.

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, columns])	Read SQL query or database table into a DataFrame.

Pandas API on Spark pyspark.pandas.range