Input/Output¶
Pickling¶
read_pickle (path[, compression]) |
Load pickled pandas object (or any object) from file. |
Flat File¶
read_table (filepath_or_buffer[, sep, …]) |
(DEPRECATED) Read general delimited file into DataFrame. |
read_csv (filepath_or_buffer[, sep, …]) |
Read a comma-separated values (csv) file into DataFrame. |
read_fwf (filepath_or_buffer[, colspecs, …]) |
Read a table of fixed-width formatted lines into DataFrame. |
read_msgpack (path_or_buf[, encoding, iterator]) |
Load msgpack pandas object from the specified file path |
Clipboard¶
read_clipboard ([sep]) |
Read text from clipboard and pass to read_csv. |
Excel¶
read_excel (io[, sheet_name, header, names, …]) |
Read an Excel file into a pandas DataFrame. |
ExcelFile.parse ([sheet_name, header, names, …]) |
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[, record_path, meta, …]) |
Normalize semi-structured JSON data into a flat table. |
build_table_schema (data[, index, …]) |
Create a Table schema from data . |
HDFStore: PyTables (HDF5)¶
read_hdf (path_or_buf[, key, mode]) |
Read from the store, close it if we opened it. |
HDFStore.put (key, value[, format, append]) |
Store object in HDFStore |
HDFStore.append (key, value[, format, …]) |
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 () |
Return a (potentially unordered) list of the keys corresponding to the objects stored in the HDFStore. |
HDFStore.groups () |
return a list of all the top-level nodes (that are not themselves a pandas storage object) |
HDFStore.walk ([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. |
STATA¶
read_stata (filepath_or_buffer[, …]) |
Read Stata file into DataFrame. |
StataReader.data (**kwargs) |
(DEPRECATED) Reads observations from Stata file, converting them into a dataframe |
StataReader.data_label () |
Returns data label of Stata file |
StataReader.value_labels () |
Returns a dict, associating each variable name a dict, associating each value its corresponding label |
StataReader.variable_labels () |
Returns variable labels as a dict, associating each variable name with corresponding label |
StataWriter.write_file () |