Yet another way to substitute values into strings, using placeholders like The string module contains a Template class that offers hello = 'hello, world \n ' > hellos = repr ( hello ) > print ( hellos ) 'hello, world\n' > # The argument to repr() may be any Python object. > # The repr() of a string adds string quotes and backslashes. Particular, have two distinct representations. Many values, such as numbers or structures like lists andĭictionaries, have the same representation using either function. Representation for human consumption, str() will return the same value as For objects which don’t have a particular Which can be read by the interpreter (or will force a Synta圎rror if The str() function is meant to return representations of values which areįairly human-readable, while repr() is meant to generate representations Variables for debugging purposes, you can convert any value to a string with When you don’t need fancy output but just want a quick display of some String type has some methods that perform useful operations for padding format ( yes_votes, percentage ) ' 42572654 YES votes 49.67%'įinally, you can do all the string handling yourself by using string slicing andĬoncatenation operations to create any layout you can imagine. If any of the passed column names do not exist. drop_columns ( self, columns ) ¶ĭrop one or more columns and return a new table. Parameters : columns str or listįield name(s) referencing existing column(s). combine_chunks () pyarrow.Table n_legs: int64 animals: string - n_legs: ] animals: ] drop ( self, columns ) ¶Īlias of Table.drop_columns, but kept for backwards compatibility. table (, names = names ) > table pyarrow.Table n_legs: int64 animals: string - n_legs: ,] animals: ,] > table. chunked_array (, ]) > names = > table = pa. column Array, list of Array, or values coercible to arrays If a string is passed then the type is deduced from the columnĭata. Total number of bytes consumed by the elements of the table.ĭimensions of the table: (#rows, #columns).Īdd_column ( self, int i, field_, column ) ¶Ī new table is returned with the column added, the original table Return human-readable string representation of Table. To_pandas(self)Ĭonvert to a pandas-compatible NumPy array or DataFrame, as appropriateĬonvert the Table to a dict or OrderedDict.Ĭonvert the Table to a list of rows / dictionaries.Ĭonvert the Table to a RecordBatchReader. Sort the table by one or multiple columns.Ĭonvert Table to a list of RecordBatch objects. Replace_schema_metadata(self)Ĭreate shallow copy of table by replacing schema key-value metadata with the indicated new metadata (which may be None), which deletes any existing metadata. Perform a join between this table and another one.Ĭreate new Table with the indicated column removed.Ĭreate new table with columns renamed to provided names. Iterator over all columns in their numerical order. The sum of bytes in each buffer referenced by the table.ĭeclare a grouping over the columns of the table. Select a schema field by its column name or numeric index.įilter(self, mask)įlatten(self, MemoryPool memory_pool=None)įrom_arrays(arrays)įrom_batches(batches, Schema schema=None)Ĭonstruct a Table from a sequence or iterator of Arrow RecordBatches.įrom_pandas(type cls, df, Schema schema=None)Ĭonvert pandas.DataFrame to an Arrow Table.Ĭonstruct a Table from Arrow arrays or columns.Ĭonstruct a Table from list of rows / dictionaries. Make a new table by combining the chunks this table has.ĭrop one or more columns and return a new table.Ĭheck if contents of two tables are equal. Select a column by its column name, or numeric index.Ĭombine_chunks(self, MemoryPool memory_pool=None) table (, names = names ) pyarrow.Table n_legs: int64 animals: string - n_legs: ] animals: ] _init_ ( * args, ** kwargs ) ¶Ĭast(self, Schema target_schema) Reading and Writing the Apache Parquet Format Reading and Writing the Apache ORC Format
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