read_pickle(filepath_or_buffer, …)
read_pickle
Load pickled pandas object (or any object) from file.
read_table(filepath_or_buffer, pathlib.Path, …)
read_table
Read general delimited file into DataFrame.
read_csv(filepath_or_buffer, pathlib.Path, …)
read_csv
Read a comma-separated values (csv) file into DataFrame.
read_fwf(filepath_or_buffer, pathlib.Path, …)
read_fwf
Read a table of fixed-width formatted lines into DataFrame.
read_clipboard([sep])
read_clipboard
Read text from clipboard and pass to read_csv.
read_excel(io[, sheet_name, header, names, …])
read_excel
Read an Excel file into a pandas DataFrame.
ExcelFile.parse(self[, sheet_name, header, …])
ExcelFile.parse
Parse specified sheet(s) into a DataFrame.
ExcelWriter(path[, engine, date_format, …])
ExcelWriter
Class for writing DataFrame objects into excel sheets.
read_json([path_or_buf, orient, typ, dtype, …])
read_json
Convert a JSON string to pandas object.
json_normalize(data, List[Dict]], …)
json_normalize
Normalize semi-structured JSON data into a flat table.
build_table_schema(data[, index, …])
build_table_schema
Create a Table schema from data.
data
read_html(io[, match, flavor, header, …])
read_html
Read HTML tables into a list of DataFrame objects.
list
DataFrame
read_hdf(path_or_buf[, key, where, columns, …])
read_hdf
Read from the store, close it if we opened it.
HDFStore.put(self, key, value[, format, …])
HDFStore.put
Store object in HDFStore.
HDFStore.append(self, key, value[, format, …])
HDFStore.append
Append to Table in file.
HDFStore.get(self, key)
HDFStore.get
Retrieve pandas object stored in file.
HDFStore.select(self, key[, where, start, …])
HDFStore.select
Retrieve pandas object stored in file, optionally based on where criteria.
HDFStore.info(self)
HDFStore.info
Print detailed information on the store.
HDFStore.keys(self)
HDFStore.keys
Return a list of keys corresponding to objects stored in HDFStore.
HDFStore.groups(self)
HDFStore.groups
Return a list of all the top-level nodes.
HDFStore.walk(self[, where])
HDFStore.walk
Walk the pytables group hierarchy for pandas objects.
read_feather(path[, columns])
read_feather
Load a feather-format object from the file path.
read_parquet(path, engine[, columns])
read_parquet
Load a parquet object from the file path, returning a DataFrame.
read_orc(path, pathlib.Path, IO[~AnyStr]], …)
read_orc
Load an ORC object from the file path, returning a DataFrame.
read_sas(filepath_or_buffer[, format, …])
read_sas
Read SAS files stored as either XPORT or SAS7BDAT format files.
read_spss(path, pathlib.Path], usecols, …)
read_spss
Load an SPSS file from the file path, returning a DataFrame.
read_sql_table(table_name, con[, schema, …])
read_sql_table
Read SQL database table into a DataFrame.
read_sql_query(sql, con[, index_col, …])
read_sql_query
Read SQL query into a DataFrame.
read_sql(sql, con[, index_col, …])
read_sql
Read SQL query or database table into a DataFrame.
read_gbq(query, project_id, …[, …])
read_gbq
Load data from Google BigQuery.
read_stata(filepath_or_buffer[, …])
read_stata
Read Stata file into DataFrame.
StataReader.data_label
Return data label of Stata file.
StataReader.value_labels(self)
StataReader.value_labels
Return a dict, associating each variable name a dict, associating each value its corresponding label.
StataReader.variable_labels(self)
StataReader.variable_labels
Return variable labels as a dict, associating each variable name with corresponding label.
StataWriter.write_file(self)
StataWriter.write_file