FM / __pycache_

/usr/local/lib64/python3.6/site-packages/pandas/io/__pycache__/

/usr/local/lib64/python3.6/site-packages/pandas/io/__pycache__

Name	Size	Mode	Actions
api.cpython-36.pyc	1096	0644	edit dl rm
clipboards.cpython-36.pyc	3392	0644	edit dl rm
common.cpython-36.pyc	14064	0644	edit dl rm
date_converters.cpython-36.pyc	1947	0644	edit dl rm
feather_format.cpython-36.pyc	2936	0644	edit dl rm
gbq.cpython-36.pyc	7459	0644	edit dl rm
html.cpython-36.pyc	31977	0644	edit dl rm
orc.cpython-36.pyc	1802	0644	edit dl rm
parquet.cpython-36.pyc	9500	0644	edit dl rm
parsers.cpython-36.pyc	88200	0644	edit dl rm
pickle.cpython-36.pyc	5679	0644	edit dl rm
pytables.cpython-36.pyc	130805	0644	edit dl rm
spss.cpython-36.pyc	1328	0644	edit dl rm
sql.cpython-36.pyc	52283	0644	edit dl rm
stata.cpython-36.pyc	97563	0644	edit dl rm
__init__.cpython-36.pyc	145	0644	edit dl rm

Edit: /usr/local/lib64/python3.6/site-packages/pandas/io/__pycache__/stata.cpython-36.pyc (97563B)

3 :%Eg��@sdZddlmZddlZddlmZmZddlZddlm Z ddl Z ddlZddlm Z mZmZmZmZmZmZmZmZmZddlZddlmZddlZddlmZdd lmZdd l m!Z!m"Z"ddl#m$Z$ddl%m&Z&m'Z'm(Z(dd l)m*Z*m+Z+m,Z,m-Z-m.Z.m/Z/m0Z0m1Z1ddl2m3Z3ddl4m5Z5ddl6m7Z7ddl8m9Z9m:Z:m;Z;mdZ?dZ@dZAdZBdZCde?�de@�deA�deB�deC�d�ZDde?�de@�d�ZEde?�de@�deA�deC�d� ZFd d!d"d#d$d%d&d'd(g ZGejd)d*d*�ZHe7d+�d,d-�ZIe7eJe7d.�d/d0�ZKd1ZLGd2d3�d3eM�ZNd4ZOGd5d6�d6eM�ZPd7ZQGd8d9�d9eM�ZRd:ZSGd;d<�d�d?d@�ZVGdAdB�dB�ZWGdCdD�dD�ZXGdEdF�dF�ZYGdGdH�dHeYejZ�Z[e$eD�dqe!e\e\eeJe\e\eeeJe\ee]e\ee3e[fdK�dLdM��Z^e!eeJeeJeJfdfeee\eeeJeeJeJfffdN�dOdP�Z_eJeJdQ�dRdS�Z`ee]edT�dUdV�ZaeJejbdW�dXdY�Zceee"edZ�d[d\�Zdejbe7e]d]�d^d_�Zedre7e]e\eJda�dbdc�ZfGddde�deeY�Zgejbe7e\e]df�dgdh�ZheeJeife]eidT�didj�ZjGdkdl�dl�ZkGdmdn�dneg�ZlGdodp�dpel�ZmdS)sa� Module contains tools for processing Stata files into DataFrames The StataReader below was originally written by Joe Presbrey as part of PyDTA. 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If False, missing values are replaced with nan. If True, columns containing missing values are returned with object data types and missing values are represented by StataMissingValue objects. preserve_dtypes : bool, default True Preserve Stata datatypes. If False, numeric data are upcast to pandas default types for foreign data (float64 or int64). columns : list or None Columns to retain. Columns will be returned in the given order. None returns all columns. order_categoricals : bool, default True Flag indicating whether converted categorical data are ordered.zzchunksize : int, default None Return StataReader object for iterations, returns chunks with given number of lines.z=iterator : bool, default False Return StataReader object.z�Notes ----- Categorical variables read through an iterator may not have the same categories and dtype. This occurs when a variable stored in a DTA file is associated to an incomplete set of value labels that only label a strict subset of the values.a? Read Stata file into DataFrame. Parameters ---------- filepath_or_buffer : str, path object or file-like object Any valid string path is acceptable. The string could be a URL. Valid URL schemes include http, ftp, s3, and file. For file URLs, a host is expected. A local file could be: ``file://localhost/path/to/table.dta``. If you want to pass in a path object, pandas accepts any ``os.PathLike``. By file-like object, we refer to objects with a ``read()`` method, such as a file handler (e.g. via builtin ``open`` function) or ``StringIO``. � z� Returns ------- DataFrame or StataReader See Also -------- io.stata.StataReader : Low-level reader for Stata data files. 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Each label must be 80 characters or smaller. compression : str or dict, default 'infer' For on-the-fly compression of the output dta. If string, specifies compression mode. If dict, value at key 'method' specifies compression mode. Compression mode must be one of {'infer', 'gzip', 'bz2', 'zip', 'xz', None}. If compression mode is 'infer' and `fname` is path-like, then detect compression from the following extensions: '.gz', '.bz2', '.zip', or '.xz' (otherwise no compression). If dict and compression mode is one of {'zip', 'gzip', 'bz2'}, or inferred as one of the above, other entries passed as additional compression options. .. versionadded:: 1.1.0 Returns ------- writer : StataWriter instance The StataWriter instance has a write_file method, which will write the file to the given `fname`. 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These differ in how the GSO is stored. 118 and 119 store the GSO lookup value as a uint32 and a uint64, while 117 uses two uint32s. 118 and 119 also encode all strings as unicode which is required by the format. 117 uses 'latin-1' a fixed width encoding that extends the 7-bit ascii table with an additional 128 characters. r�N)�dfrfr�r�cCs�|dkrtd��||_||_||_ddi|_|dkr:tj}t|�|_d}d}d |_ |dkrjd }d}d|_ n|dkrxd}nd }ddd||_ ||_||_dS)Nr�r�r�z,Only dta versions 117, 118 and 119 supportedr�rr�r zutf-8razlatin-1rfr�rer�)r�r�r�)rr) rIZ_dta_verr�rf� _gso_tabler|r�r{rNr��_o_offet�_gso_o_type�_gso_v_type)r�r�rfr�r�Z gso_v_typeZ gso_o_typeZo_sizer4r4r5r�s, zStataStrLWriter.__init__)r�r+cCs|\}}||j|S)N)r�)r�r�r�rfr4r4r5�_convert_key4szStataStrLWriter._convert_key)r+cs|j}|j}t|j��||j}�fdd�|jD�}tj|jtjd�}x�t|j ��D]|\}\}}xnt|�D]b\} \} }|| }|dkr�dn|}|j |d�} | dkr�|d|df} | ||<|j| �||| f<qjWqTWx*t|j�D]\}} |dd�|f|| <q�W||fS)a� Generates the GSO lookup table for the DataFrame Returns ------- gso_table : dict Ordered dictionary using the string found as keys and their lookup position (v,o) as values gso_df : DataFrame DataFrame where strl columns have been converted to (v,o) values Notes ----- Modifies the DataFrame in-place. The DataFrame returned encodes the (v,o) values as uint64s. The encoding depends on the dta version, and can be expressed as enc = v + o * 2 ** (o_size * 8) so that v is stored in the lower bits and o is in the upper bits. o_size is * 117: 4 * 118: 6 * 119: 5 csg|]}|�j|�f�qSr4)r/)r1r�)rfr4r5r6Ysz2StataStrLWriter.generate_table..)rTNr�r*)r�r�r�rfri�emptyrir�r�Ziterrows�getr�)r�� gso_tableZgso_df�selectedZ col_indexrrf�idx�rowrr�r�r�r�r�r4)rfr5�generate_table8s$ zStataStrLWriter.generate_table)r�r+cCst�}tdd�}tj|jdd�}tj|jdd�}|j|j}|j|j}|jd}x�|j�D]�\} } | d krrq`| \}}|j|�|jtj||��|jtj||��|j|�t| d�} |jtj|t | �d��|j| �|j|�q`W|j d�|j�S) a� Generates the binary blob of GSOs that is written to the dta file. Parameters ---------- gso_table : dict Ordered dictionary (str, vo) Returns ------- gso : bytes Binary content of dta file to be placed between strl tags Notes ----- Output format depends on dta version. 117 uses two uint32s to express v and o while 118+ uses a uint32 for v and a uint64 for o. r��asciir�r�rr�zutf-8r*)rr)rr�r�r�rNr�r�rcr�r�r�r�)r�r�r�ZgsoZgso_type�nullZv_typeZo_typeZlen_typeZstrlZvor�rfZutf8_stringr4r4r5� generate_blobks* zStataStrLWriter.generate_blob)r�N)r�r�r�r�r!r r�rCrr�rr�r r�r�r�r4r4r4r5r�� s&3r�cs�eZdZdZdZdZd6eeee e efeeeee j eeee e efeee eeeeefdfd� �fdd � Zeeeefeed �dd��Zedd �dd�Zd7eeee j dd�dd�Zdd�dd�Zdd�dd�Zdd�dd�Zdd�dd�Zdd�dd�Zdd�dd�Zdd�d d!�Zdd�d"d#�Zdd�d$d%�Zdd�d&d'�Z dd�d(d)�Z!dd�d*d+�Z"dd�d,d-�Z#dd�d.d/�Z$eed0�d1d2�Z%e&dd3�d4d5�Z'�Z(S)8�StataWriter117a� A class for writing Stata binary dta files in Stata 13 format (117) .. versionadded:: 0.23.0 Parameters ---------- fname : path (string), buffer or path object string, path object (pathlib.Path or py._path.local.LocalPath) or object implementing a binary write() functions. If using a buffer then the buffer will not be automatically closed after the file is written. data : DataFrame Input to save convert_dates : dict Dictionary mapping columns containing datetime types to stata internal format to use when writing the dates. Options are 'tc', 'td', 'tm', 'tw', 'th', 'tq', 'ty'. Column can be either an integer or a name. Datetime columns that do not have a conversion type specified will be converted to 'tc'. Raises NotImplementedError if a datetime column has timezone information write_index : bool Write the index to Stata dataset. byteorder : str Can be ">", "<", "little", or "big". default is `sys.byteorder` time_stamp : datetime A datetime to use as file creation date. Default is the current time data_label : str A label for the data set. Must be 80 characters or smaller. variable_labels : dict Dictionary containing columns as keys and variable labels as values. Each label must be 80 characters or smaller. convert_strl : list List of columns names to convert to Stata StrL format. Columns with more than 2045 characters are automatically written as StrL. Smaller columns can be converted by including the column name. Using StrLs can reduce output file size when strings are longer than 8 characters, and either frequently repeated or sparse. compression : str or dict, default 'infer' For on-the-fly compression of the output dta. If string, specifies compression mode. If dict, value at key 'method' specifies compression mode. Compression mode must be one of {'infer', 'gzip', 'bz2', 'zip', 'xz', None}. If compression mode is 'infer' and `fname` is path-like, then detect compression from the following extensions: '.gz', '.bz2', '.zip', or '.xz' (otherwise no compression). If dict and compression mode is one of {'zip', 'gzip', 'bz2'}, or inferred as one of the above, other entries passed as additional compression options. .. versionadded:: 1.1.0 Returns ------- writer : StataWriter117 instance The StataWriter117 instance has a write_file method, which will write the file to the given `fname`. Raises ------ NotImplementedError * If datetimes contain timezone information ValueError * Columns listed in convert_dates are neither datetime64[ns] or datetime.datetime * Column dtype is not representable in Stata * Column listed in convert_dates is not in DataFrame * Categorical label contains more than 32,000 characters Examples -------- >>> from pandas.io.stata import StataWriter117 >>> data = pd.DataFrame([[1.0, 1, 'a']], columns=['a', 'b', 'c']) >>> writer = StataWriter117('./data_file.dta', data) >>> writer.write_file() Directly write a zip file >>> compression = {"method": "zip", "archive_name": "data_file.dta"} >>> writer = StataWriter117('./data_file.zip', data, compression=compression) >>> writer.write_file() Or with long strings stored in strl format >>> data = pd.DataFrame([['A relatively long string'], [''], ['']], ... columns=['strls']) >>> writer = StataWriter117('./data_file_with_long_strings.dta', data, ... convert_strl=['strls']) >>> writer.write_file() i�r�NTrF) r&r�rarGr�r�rrrpr'csHg|_| dk r|jj| �t�j||||||||| d� i|_d|_dS)N)r�r�rrr'�)rn�extendrjr��_map� _strl_blob)r�r&r�rarGr�r�rrrpr')r�r4r5r�szStataWriter117.__init__)r��tagr+cCs<t|t�rt|d�}td|dd�|td|dd�S)zSurround val with zutf-8r�r�zzutf-8�releaser�ZMSFZLSFr�r�r�r��Kr�r �NNrr�r�rz"time_stamp should be datetime typer�r�r�r�r�r�r�r�r�r�r�r�cSsi|]\}}||d�qS)r*r4)r1r�r<r4r4r5r�bsz0StataWriter117._write_header..z%d z %Y %H:%M�� timestampr�header)rNrTr�rr�r�r��_dta_versionr�r�r�r�r�r�r�r0r�r�rIr�r�r<r�r�)r�rr�r�r�r�Z nobs_sizerZ encoded_labelZ label_sizeZ label_lenr�r�r�Zstata_tsr4r4r5rr3sJ zStataWriter117._write_header)r+cCs�|jdk st�|jsDtdd|jj�fddddddddddddf�|_|jj|jd�t�}x*|jj�D]}|jt j |jd|��qhW|jd�|j|j |j�d��dS)z� Called twice during file write. The first populates the values in the map with 0s. The second call writes the final map locations when all blocks have been written. 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Unicode is also supported in value labels, variable labels and the dataset label. Format 119 is automatically used if the file contains more than 32,767 variables. .. versionadded:: 1.0.0 Parameters ---------- fname : path (string), buffer or path object string, path object (pathlib.Path or py._path.local.LocalPath) or object implementing a binary write() functions. If using a buffer then the buffer will not be automatically closed after the file is written. data : DataFrame Input to save convert_dates : dict, default None Dictionary mapping columns containing datetime types to stata internal format to use when writing the dates. Options are 'tc', 'td', 'tm', 'tw', 'th', 'tq', 'ty'. Column can be either an integer or a name. Datetime columns that do not have a conversion type specified will be converted to 'tc'. Raises NotImplementedError if a datetime column has timezone information write_index : bool, default True Write the index to Stata dataset. byteorder : str, default None Can be ">", "<", "little", or "big". default is `sys.byteorder` time_stamp : datetime, default None A datetime to use as file creation date. Default is the current time data_label : str, default None A label for the data set. Must be 80 characters or smaller. variable_labels : dict, default None Dictionary containing columns as keys and variable labels as values. Each label must be 80 characters or smaller. convert_strl : list, default None List of columns names to convert to Stata StrL format. Columns with more than 2045 characters are automatically written as StrL. Smaller columns can be converted by including the column name. Using StrLs can reduce output file size when strings are longer than 8 characters, and either frequently repeated or sparse. version : int, default None The dta version to use. By default, uses the size of data to determine the version. 118 is used if data.shape[1] <= 32767, and 119 is used for storing larger DataFrames. compression : str or dict, default 'infer' For on-the-fly compression of the output dta. If string, specifies compression mode. If dict, value at key 'method' specifies compression mode. Compression mode must be one of {'infer', 'gzip', 'bz2', 'zip', 'xz', None}. If compression mode is 'infer' and `fname` is path-like, then detect compression from the following extensions: '.gz', '.bz2', '.zip', or '.xz' (otherwise no compression). If dict and compression mode is one of {'zip', 'gzip', 'bz2'}, or inferred as one of the above, other entries passed as additional compression options. .. versionadded:: 1.1.0 Returns ------- StataWriterUTF8 The instance has a write_file method, which will write the file to the given `fname`. Raises ------ NotImplementedError * If datetimes contain timezone information ValueError * Columns listed in convert_dates are neither datetime64[ns] or datetime.datetime * Column dtype is not representable in Stata * Column listed in convert_dates is not in DataFrame * Categorical label contains more than 32,000 characters Examples -------- Using Unicode data and column names >>> from pandas.io.stata import StataWriterUTF8 >>> data = pd.DataFrame([[1.0, 1, 'ᴬ']], columns=['a', 'β', 'ĉ']) >>> writer = StataWriterUTF8('./data_file.dta', data) >>> writer.write_file() Directly write a zip file >>> compression = {"method": "zip", "archive_name": "data_file.dta"} >>> writer = StataWriterUTF8('./data_file.zip', data, compression=compression) >>> writer.write_file() Or with long strings stored in strl format >>> data = pd.DataFrame([['ᴀ relatively long ŝtring'], [''], ['']], ... columns=['strls']) >>> writer = StataWriterUTF8('./data_file_with_long_strings.dta', data, ... convert_strl=['strls']) >>> writer.write_file() zutf-8NTrF)r&r�rarGr�r�rrrpr�r'csz| dkr |jddkrdnd} n0| dkr2td��n| dkrP|jddkrPtd��t�j||||||||| |d� | |_dS) Nr*i�r�r�z"version must be either 118 or 119.zKYou must use version 119 for data sets containing more than32,767 variables)rarGr�r�rrrpr')r�r�)rirIrjr�r�)r�r&r�rarGr�r�rrrpr�r')r�r4r5r�� s& zStataWriterUTF8.__init__)r�r+cCs~xx|D]p}t|�dkrN|dks&|dkrN|dks6|dkrN|dksF|dkrN|dksjdt|�kodd knr|j|d�}qW|S) a� Validate variable names for Stata export. Parameters ---------- name : str Variable name Returns ------- str The validated name with invalid characters replaced with underscores. Notes ----- Stata 118+ support most unicode characters. 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