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.