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#
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(path_or_buffer[, engine, ...]) |
Class for parsing tabular Excel sheets into DataFrame objects. |
| ExcelFile.book |
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| ExcelFile.sheet_names |
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| 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, ...]) |
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. |
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, header, ...]) |
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, dtype_backend, ...]) |
Load an ORC object from the file path, returning a DataFrame. |
| DataFrame.to_orc([path, engine, index, ...]) |
Write a DataFrame to the ORC format. |
SAS#
| read_sas(filepath_or_buffer, *[, format, ...]) |
Read SAS files stored as either XPORT or SAS7BDAT format files. |
SPSS#
| read_spss(path[, usecols, ...]) |
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, ...]) |
(DEPRECATED) 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. |