Input/output
read_pickle(path[, compression]) |
Load pickled pandas object (or any object) from file. |
Flat file
read_table(filepath_or_buffer, pathlib.Path, …) |
Read general delimited file into DataFrame. |
read_csv(filepath_or_buffer, pathlib.Path, …) |
Read a comma-separated values (csv) file into DataFrame. |
read_fwf(filepath_or_buffer, pathlib.Path, …) |
Read a table of fixed-width formatted lines into DataFrame. |
read_msgpack(path_or_buf[, encoding, iterator]) |
(DEPRECATED) Load msgpack pandas object from the specified file path. |
Clipboard
Excel
read_excel(io[, sheet_name, header, names, …]) |
Read an Excel file into a pandas DataFrame. |
ExcelFile.parse(self[, sheet_name, header, …]) |
Parse specified sheet(s) into a DataFrame |
ExcelWriter(path[, engine, date_format, …]) |
Class for writing DataFrame objects into excel sheets, default is to use xlwt for xls, openpyxl for xlsx. |
JSON
read_json([path_or_buf, orient, typ, dtype, …]) |
Convert a JSON string to pandas object. |
json_normalize(data, List[Dict]], …) |
Normalize semi-structured JSON data into a flat table. |
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. |
HDFStore: PyTables (HDF5)
read_hdf(path_or_buf[, key, mode]) |
Read from the store, close it if we opened it. |
HDFStore.put(self, key, value[, format, append]) |
Store object in HDFStore |
HDFStore.append(self, key, value[, format, …]) |
Append to Table in file. |
HDFStore.get(self, key) |
Retrieve pandas object stored in file |
HDFStore.select(self, key[, where, start, …]) |
Retrieve pandas object stored in file, optionally based on where criteria |
HDFStore.info(self) |
Print detailed information on the store. |
HDFStore.keys(self) |
Return a (potentially unordered) list of the keys corresponding to the objects stored in the HDFStore. |
HDFStore.groups(self) |
return a list of all the top-level nodes (that are not themselves a pandas storage object) |
HDFStore.walk(self[, where]) |
Walk the pytables group hierarchy for pandas objects |
Feather
read_feather(path[, columns, use_threads]) |
Load a feather-format object from the file path. |
Parquet
read_parquet(path[, engine, columns]) |
Load a parquet 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. |
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. |
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. |