'VfiUdZddlmZddlmZddlmZmZddlmZddl Z ddl Z ddl Z ddl m Z mZmZmZmZmZddlZddlZddlmZdd lmZdd lmZdd lmZmZmZm Z dd l!m"Z"m#Z#dd l$m%Z%ddl&m'Z'ddl(m)Z)m*Z*m+Z+ddl,m-Z-ddl.m/Z/m0Z0m1Z1m2Z2m3Z3m4Z4m5Z5ddl6m7Z7ddl8m9Z9ddl:m;Z;ddlm?Z?ddl@mAZAer$ddlBmCZCmDZDddlEmFZFddl mGZGddlHmIZImJZJmKZKmLZLmMZMmNZNdZOdZPdZQdZRd ZSd!ZTd"ePd#eQd#eRd#eSd#e?d$d%zd#e?d&d'eTd(ZUd)ePd#eQd*ZVd+ePd#eQd#eRd#e?d$d#e?d&d,eTd# ZWgd-ZXed.d/d/ZYd0eZd1<dd7Z[dd8Z\d9Z]d0eZd:<d;Z^d0eZd<<d=Z_d0eZd><d?Z`d0eZd@<dAZad0eZdB<ddEZbGdFdGZcGdHdIecZdGdJdKZeGdLdMZfGdNdOefejgZhe"eUdPdPddQdPddPddQdRddS ddfZiddhZjddmZkddoZlddsZmddvZn dddzZoe#e?d&e?d{d|z}Gd~defZpddZqddZrGddZsGddepZtGddetZudS)a Module contains tools for processing Stata files into DataFrames The StataReader below was originally written by Joe Presbrey as part of PyDTA. It has been extended and improved by Skipper Seabold from the Statsmodels project who also developed the StataWriter and was finally added to pandas in a once again improved version. You can find more information on http://presbrey.mit.edu/PyDTA and https://www.statsmodels.org/devel/ ) annotations)abc)datetime timedelta)BytesION)IO TYPE_CHECKINGAnyStrCallableFinalcast)lib) infer_dtype)max_len_string_array)CategoricalConversionWarningInvalidColumnNamePossiblePrecisionLossValueLabelTypeMismatch)Appenderdoc)find_stack_level)ExtensionDtype) ensure_objectis_numeric_dtypeis_string_dtype)CategoricalDtype) Categorical DatetimeIndexNaT Timestampisna to_datetime to_timedelta) DataFrame)Index) RangeIndex)Series) _shared_docs) get_handle)HashableSequence) TracebackType)Literal)CompressionOptionsFilePath ReadBufferSelfStorageOptions WriteBufferzVersion of given Stata file is {version}. pandas supports importing versions 105, 108, 111 (Stata 7SE), 113 (Stata 8/9), 114 (Stata 10/11), 115 (Stata 12), 117 (Stata 13), 118 (Stata 14/15/16),and 119 (Stata 15/16, over 32,767 variables).zconvert_dates : bool, default True Convert date variables to DataFrame time values. convert_categoricals : bool, default True Read value labels and convert columns to Categorical/Factor variables.aindex_col : str, optional Column to set as index. convert_missing : bool, default False Flag indicating whether to convert missing values to their Stata representations. 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.zNotes ----- 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 handle (e.g. via builtin ``open`` function) or ``StringIO``.  decompression_optionsfilepath_or_bufferstorage_optionsz Returns ------- DataFrame or pandas.api.typing.StataReader See Also -------- io.stata.StataReader : Low-level reader for Stata data files. DataFrame.to_stata: Export Stata data files. a Examples -------- Creating a dummy stata for this example >>> df = pd.DataFrame({'animal': ['falcon', 'parrot', 'falcon', 'parrot'], ... 'speed': [350, 18, 361, 15]}) # doctest: +SKIP >>> df.to_stata('animals.dta') # doctest: +SKIP Read a Stata dta file: >>> df = pd.read_stata('animals.dta') # doctest: +SKIP Read a Stata dta file in 10,000 line chunks: >>> values = np.random.randint(0, 10, size=(20_000, 1), dtype="uint8") # doctest: +SKIP >>> df = pd.DataFrame(values, columns=["i"]) # doctest: +SKIP >>> df.to_stata('filename.dta') # doctest: +SKIP >>> with pd.read_stata('filename.dta', chunksize=10000) as itr: # doctest: +SKIP >>> for chunk in itr: ... # Operate on a single chunk, e.g., chunk.mean() ... pass # doctest: +SKIP zReads observations from Stata file, converting them into a dataframe Parameters ---------- nrows : int Number of lines to read from data file, if None read whole file. z Returns ------- DataFrame zClass for reading Stata dta files. Parameters ---------- path_or_buf : path (string), buffer or path object string, path object (pathlib.Path or py._path.local.LocalPath) or object implementing a binary read() functions. z ) %tc%tC%td%d%tw%tm%tq%th%tyr stata_epochdatesr'fmtstrreturnctjjtjjctjt dddz jtjt dddz jdzdzdzdzdzdzd$fd }d$fd }d$fd }t j|}d }|r d }d |j |<| t j }| drt}|}|||d} n| drFtjdt!t#|t$} |r t&| |<| S| drt}|} ||| d} nB| dr(tj|dzz} |dzdz} || | } n| dr'tj|dzz} |dzdz} || | } n| dr*tj|dzz} |dzdzdz} || | } n| dr*tj|dzz} |dzd zdz} || | } nK| d!r#|} t j|}|| |} nt+d"|d#|r t&| |<| S)%a Convert from SIF to datetime. https://www.stata.com/help.cgi?datetime Parameters ---------- dates : Series The Stata Internal Format date to convert to datetime according to fmt fmt : str The format to convert to. Can be, tc, td, tw, tm, tq, th, ty Returns Returns ------- converted : Series The converted dates Examples -------- >>> dates = pd.Series([52]) >>> _stata_elapsed_date_to_datetime_vec(dates , "%tw") 0 1961-01-01 dtype: datetime64[ns] Notes ----- datetime/c - tc milliseconds since 01jan1960 00:00:00.000, assuming 86,400 s/day datetime/C - tC - NOT IMPLEMENTED milliseconds since 01jan1960 00:00:00.000, adjusted for leap seconds date - td days since 01jan1960 (01jan1960 = 0) weekly date - tw weeks since 1960w1 This assumes 52 weeks in a year, then adds 7 * remainder of the weeks. The datetime value is the start of the week in terms of days in the year, not ISO calendar weeks. monthly date - tm months since 1960m1 quarterly date - tq quarters since 1960q1 half-yearly date - th half-years since 1960h1 yearly date - ty years since 0000 rArBirGr'c|kr/|krtd|z|zdSt|dd}t dt ||D|S)z Convert year and month to datetimes, using pandas vectorized versions when the date range falls within the range supported by pandas. Otherwise it falls back to a slower but more robust method using datetime. dz%Y%mformatindexNc6g|]\}}t||dSrB)r).0yms >c:\PYTHON\DbComparer\venv\Lib\site-packages\pandas/io/stata.py zX_stata_elapsed_date_to_datetime_vec..convert_year_month_safe..,s(JJJA8Aq!,,JJJrO)maxminr"getattrr'zip)yearmonthrOMAX_YEARMIN_YEARs rUconvert_year_month_safezD_stata_elapsed_date_to_datetime_vec..convert_year_month_safe!s 88:: TXXZZ(%:%:sTzE1&AAA AD'400EJJT59I9IJJJRWXXX XrWc(|dz kr;|kr#t|dt|dzSt |dd}dt ||D}t || S) z{ Converts year (e.g. 1999) and days since the start of the year to a datetime or datetime64 Series rB%YrMdunitrONcrg|]4\}}t|ddtt|z5S)rBdays)rrint)rRrSrds rUrVzW_stata_elapsed_date_to_datetime_vec..convert_year_days_safe..7sK?Cq!Aq!!I3q66$:$:$::rWrX)rYrZr"r#r[r\r')r]rirOvaluer_r`s rUconvert_year_days_safezC_stata_elapsed_date_to_datetime_vec..convert_year_days_safe.s 88::A & &488::+@+@tD111LC4P4P4PP PD'400EGJ4QUE%u--- -rWct|dd}|dkrP|ks|krfd|D}t||Sne|dkrP|ks|krfd|D}t||Snt dt t || }|zS) z Convert base dates and deltas to datetimes, using pandas vectorized versions if the deltas satisfy restrictions required to be expressed as dates in pandas. rONrdcPg|]"}tt|z#S)rhrrjrRrdbases rUrVzS_stata_elapsed_date_to_datetime_vec..convert_delta_safe..Es/HHHA$A!7!7!77HHHrWrXmscVg|]%}tt|dzz&S)rJ) microsecondsrorps rUrVzS_stata_elapsed_date_to_datetime_vec..convert_delta_safe..Is@GHD93q66D=BBBBrWzformat not understoodre)r[rYrZr' ValueErrorr"r#) rqdeltasrfrOvalues MAX_DAY_DELTA MAX_MS_DELTA MIN_DAY_DELTA MIN_MS_DELTAs ` rUconvert_delta_safez?_stata_elapsed_date_to_datetime_vec..convert_delta_safe<s$ .. 3;;zz||m++vzz||m/K/KHHHHHHHfE22220LT\\zz||l**fjjll\.I.ILRfE2222 /J 455 54  f4000f}rWFTg?r8tcrrr9tCz9Encountered %tC format. Leaving in Stata Internal Format. stackleveldtype)r:tdr;rdrdr<tw4r=tm r>tqr?thr@tyz Date fmt  not understood)rGr')r rZr]rYrrinpisnanany_valuesastypeint64 startswithrCwarningswarnrr'objectr ones_likeru)rDrErarlr|bad_locshas_bad_valuesrqrr conv_datesrir]r^ quarter_month first_monthrxryr_rzr{r`s @@@@@@rU#_stata_elapsed_date_to_datetime_vecrs\#+Y]-?Hh]XdAq%9%99?M]XdAq%9%99?M 2%,t3L 2%,t3L Y Y Y Y Y Y Y . . . . . . .2xHN||~~&"% h LL " "E ~~m$$); ''b$77  & &%; G'))    E000  '#&Jx  0 1 1;''dC88   & &;%2+- a++D$77  & &;%2+-q ,,T599  & & ;%1*,a!+ ,,T=AA  & & ;%1*,a!#,,T599  & &;l5)) ,,T;?? 9S999:::#" 8 rWc |j ddz  d)d* fd }t|}|j |rFtj|jd rt t|j|<nt|j|<|d vr||d }|j dz }n`|dvr&tj dt|}n6|dvr||d }|j z}n|dvr1||d d }d|j tj z z|jdzz}n|dvr0||d }d|j tj z z|jzdz }n|dvr3||d }d|j tj z z|jdz dzz}ny|dvrI||d }d|j tj z z|jd kt"z}n,|d!vr||d }|j }nt%d"|d#t'|t(jd$}t-jd%d&d'}|||<t'| d(S)+aO Convert from datetime to SIF. https://www.stata.com/help.cgi?datetime Parameters ---------- dates : Series Series or array containing datetime or datetime64[ns] to convert to the Stata Internal Format given by fmt fmt : str The format to convert to. Can be, tc, td, tw, tm, tq, th, ty l"R:rJFrDr'deltaboolr]rici}tj|jdr|rT|ttdz }|jtj dz|d<|s|r-t|}|j j |d<|j j |d<|rf|jtj t|ddjtj z }| z|d <nt|d d kr|r7|jtz }d fd }tj|} | ||d<|r9|d} | jdz|d<| j|ddzz |d<|r&dd} tj| } | ||d <nt%dt'|S)NMnsrJrr]r^rcrMriFskipnarxrrGfloatc>|jzd|jzz|jzS)Ni@B)risecondsrt)r US_PER_DAYs rUfzC_datetime_to_stata_elapsed_vec..parse_dates_safe..fs#%.191DDq~UUrWc&d|jz|jzS)NrL)r]r^rs rUzJ_datetime_to_stata_elapsed_vec..parse_dates_safe..s3|t|jddz jS)NrB)rr]rirs rUgzC_datetime_to_stata_elapsed_vec..parse_dates_safe..gsA 6 66<.parse_dates_safes#  ?5; , ,&  G"Y{%;%;%C%CD%I%II '/44RX>>$F'  4t 4*511 &,1& '-3'  5"]//99KfId===$$rx..) '*4& u - - - ; ; & 3VVVVVVLOOQuXX'  B"[[)I)IJJ &.#5& '/!F)c/A'  %====LOOAeHH& 7  %((((rWrr}T)rrz'Stata Internal Format tC not supported.r)r:rr)r]rirrr)r]rrBrrrrrrrFormat z! is not a known Stata date format)rcopy(> I,,RX66S bh  x Cy}}&&$s)--//F*B*B I,,RX66S bh   GS :--$s)--//[2P2P I,,RX66S  I,,RZ88S 9==??e++tCy}}(/J/J+227IFFB rz2:. . .xS ""&&((  EcEEEIMMOOE ""u{':': I,,RZ88S "*$$;&&$>#>>U>>/:>>>  7!! 7,@cAUV.6s*+    !'))    KrWc.eZdZdZ ddd Zdd ZddZdS)StataValueLabelz Parse a categorical column and prepare formatted output Parameters ---------- catarray : Series Categorical Series to encode encoding : {"latin-1", "utf-8"} Encoding to use for value labels. latin-1catarrayr'encodingLiteral['latin-1', 'utf-8']rGNonec|dvrtd|j|_||_|jj}t ||_|dS)Nr utf-8%Only latin-1 and utf-8 are supported.) rurlabname _encodingcat categories enumerate value_labels_prepare_value_labels)selfr r rs rU__init__zStataValueLabel.__init__sa / / /DEE E} !\, %j11 ""$$$$$rWcd|_g|_d|_tjgtj|_tjgtj|_d|_g}g}|j D] }|d}t|tsTt|}tj t|jt"t%||j}||j|xjt|dzz c_||d|j||xjdz c_|jdkrt-dtj|tj|_tj|tj|_dd|jzzd|jzz|jz|_d S) zEncode value labels.rrrBri}zaStata value labels for a single variable must have a combined length less than 32,000 characters.rN)text_lentxtnrarrayroffvallenrrrFrrrrNrrrencoderappendru)roffsetsrwvlcategorys rUrz%StataValueLabel._prepare_value_labelss "8Bbh///8Bbh///  #  B$&qEHh,, x== ,33DLAA*/11  t~66H NN4= ) ) ) MMS]]Q. .MM MM"Q% HOOH % % % FFaKFFF =5 F  8G284448F"(3331tv:%DF 2T]BrW byteorderrFbytesc|j}t}d}|tj|dz|jt |jdd|}|dvrdnd}t||dz}||tdD]*}|tjd |+|tj|dz|j |tj|dz|j |j D]-}|tj|dz|.|jD]-} |tj|dz| .|jD]} || |z|S) a! Generate the binary representation of the value labels. Parameters ---------- byteorder : str Byte order of the output Returns ------- value_label : bytes Bytes containing the formatted value label iN )rutf8rBrc)rrwriterpackr#rFrr$ _pad_bytesrangerrr!r"rgetvalue) rr)r bio null_byterlab_lenr-offsetrktexts rUgenerate_value_labelz$StataValueLabel.generate_value_labels>ii  &+i#otx88999dl##CRC(//99 (999""sWgk22 'q 3 3A IIfk#y11 2 2 2 2 &+i#otv66777 &+i#ot}==>>>h < .6s !rW)key)rurrsorteditemsrr)rrrr s rUrzStataNonCatValueLabel.__init__*sq / / /DEE E !"    nn    ""$$$$$rWNr=)rrFrrFr r rGr )r?r@rArBrrCrWrUrErEs<  "1: %%%%%%%rWrEceZdZUdZiZded<dZded<eD]-Zdee<edd D]Z de d e zzee ez<.d Z d ed <e j dddZded<ed D]zZ e j de dZdee<e dkreexxe d e zz cc<e j de jdedezZe jdeZ {dZd ed<e j dddZed D]zZ e j dedZdee<e dkreexxe d e zz cc<e j de jdedezZe jdeZ{ddde j de de j deddZded<d0d"Zed1d$Zed2d%Zd1d&Zd1d'Zd3d+Zed4d.Zd/S)5ra An observation's missing value. Parameters ---------- value : {int, float} The Stata missing value code Notes ----- More information: Integer missing values make the code '.', '.a', ..., '.z' to the ranges 101 ... 127 (for int8), 32741 ... 32767 (for int16) and 2147483621 ... 2147483647 (for int32). 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FM$0CDDQGHH d$GHHK      = = = rWNr>)r?r@rArrCrWrUryrys.[ [ [ [ [ [ rWryceZdZUeZded< dcddfd ZdedZdedZdfdZ dgd&Z ded'Z ded(Z dhd*Z dhd+Zdhd,Zdhd-Zdhd.Zdhd/Zdhd0Zdhd1Zdid3Zdjd6Zded7Zded8Zdkd;Zdld=Zdld>Zdld?Zdld@ZdhdAZdmdCZdmdDZ dhdEZ!dndGZ"dodIZ#dpdKZ$dedLZ%dedMZ&dqdOZ'drdsdQZ(e)e* dtdudTZ+dvdVZ,dwdWZ-dxdYZ.dyd]Z/e0dmd^Z1e0dmd_Z2dzdaZ3d{dbZ4xZ5S)| StataReaderz IO[bytes] _path_or_bufTNFinfer path_or_bufFilePath | ReadBuffer[bytes] convert_datesrconvert_categoricals index_col str | Noneconvert_missingpreserve_dtypescolumnsSequence[str] | Noneorder_categoricals chunksize int | None compressionr.r7StorageOptions | NonerGr c *t||_||_||_||_||_||_||_||_ | |_ | |_ d|_ | |_ d|_d|_|j d|_ n*t!| t"r| dkrt%dd|_d|_d|_d|_d|_d|_d|_d|_t7t8j|_dS)NrFrBrz.chunksize must be a positive integer when set.)superr_convert_dates_convert_categoricals _index_col_convert_missing_preserve_dtypes_columns_order_categoricals_original_path_or_buf _compression_storage_optionsr _chunksize_using_iterator_enteredrrjru _close_file_missing_values_can_read_value_labels_column_selector_set_value_labels_read _data_read_dtype _lines_read_set_endiannesssysr)_native_byteorder) rrrrrrrrrrrr7 __class__s rUrzStataReader.__init__es ,%9"# / / #5 %0"' /#$ ? "DOOIs++ OyA~~MNN N7;$&+#$)!"''+ !0!?!?rWcRt|ds|dSdS)zK Ensure the file has been opened and its header data read. rN)hasattr _open_filer_s rU _ensure_openzStataReader._ensure_opens6t^,,  OO       rWc4|js(tjdtt t |jd|jd|j}t|j dr2|j r|j |_ |j |_nV|5t|j |_ dddn #1swxYwY|j j |_||dS)z^ Open the file (with compression options, etc.), and read header information. zStataReader is being used without using a context manager. Using StataReader as a context manager is the only supported method.rrbF)r7is_textrseekableN)rrrResourceWarningrr)rrrr handlerrcloserrread _read_header _setup_dtype)rhandless rUr zStataReader._open_filesm}  MW+--        &  1)     7>: . . 77>3J3J3L3L 7 'D &}D   C C$+GN,?,?,A,A$B$B! C C C C C C C C C C C C C C C#06D   s,CCCr1cd|_|S)zenter context managerT)rr_s rU __enter__zStataReader.__enter__s  rWexc_typetype[BaseException] | None exc_valueBaseException | None tracebackTracebackType | Nonec@|jr|dSdSrc)r)rrrr s rU__exit__zStataReader.__exit__s1             rWctjdtt|jr|dSdS)zClose the handle if its open. .. deprecated: 2.0.0 The close method is not part of the public API. The only supported way to use StataReader is to use it as a context manager. zThe StataReader.close() method is not part of the public API and will be removed in a future version without notice. Using StataReader as a context manager is the only supported method.rN)rr FutureWarningrrr_s rUrzStataReader.closes`   S '))                  rWc<|jdkr d|_dSd|_dS)zC Set string encoding which depends on file version vr rN)_format_versionrr_s rU _set_encodingzStataReader._set_encodings(  # % %&DNNN$DNNNrWrjchtjd|jddS)NrrrBrrrrrr_s rU _read_int8zStataReader._read_int8*}S$"3"8"8";";<<r'r r rrB)+rrrjr(ru_version_errorrNr)r4r5r9_nvar _get_nobs_nobs_get_data_label _data_label_get_time_stamp _time_stamprA_seek_vartypes_seek_varnames_seek_sortlist _seek_formats_seek_value_label_names_get_seek_variable_labels_seek_variable_labels_data_location _seek_strls_seek_value_labels _get_dtypes_typlist _dtyplistseek _get_varlist_varlistrG_srtlist _get_fmtlist_fmtlist _get_lbllist_lbllist_get_variable_labels_variable_labelsr_s rUrJzStataReader._read_new_header s r""""4#4#9#9!#<#<==   6 6^224;O2PPQQ Q  r"""!%!2!7!7!:!:f!D!D### r"""#'#73#>#>D     DDUDUDWDW  q!!!^^%%  r"""//11 r"""//11 r""" q!!! q!!!"..0025"..0025"..0025!--//!3'+'7'7'9'9B'>$&*%C%C%E%E" q!!!"..0014++--1"&"2"2"4"4r"9(,(8(89L(M(M% t~ t2333))++  t2333..tzA~>>ssC  t1222))++  t;<<<))++  t9::: $ 9 9 ; ;rW seek_vartypes,tuple[list[int | str], list[str | np.dtype]]c|j|g}g}t|jD]}|}|dkr8|||t |T ||j|||j|#t$r}td|d|d}~wwxYw||fS)Ncannot convert stata types []) rrtr5r`r5r%rFrrKeyErrorru)rr~typlistdtyplist_typerrs rUrqzStataReader._get_dtypesEs }---tz"" U UA##%%Cd{{s###C))))UNN4#4S#9:::OOD$6s$;<<<<UUU$%JC%J%J%JKKQTTU  sAC  C,C''C, list[str]cfjdkrdndfdtjDS)Nr'!cjg|]/}j0SrC_decoderrrRrrrrs rUrVz,StataReader._get_varlist..\6SSSA T.33A6677SSSrWr(r5r`rrrs`@rUruzStataReader._get_varlistYsA&,,BB#SSSSStzARARSSSSrWcjdkrdnjdkrdnjdkrdndfdtjDS) Nr'9q1hrrcjg|]/}j0SrCrrs rUrVz,StataReader._get_fmtlist..irrWrrs`@rUrxzStataReader._get_fmtlist_so  3 & &AA  !C ' 'AA  !C ' 'AAASSSSStzARARSSSSrWcjdkrdnjdkrdndfdtjDS)Nr'rrrr\cjg|]/}j0SrCrrs rUrVz,StataReader._get_lbllist..srrWrrs`@rUrzzStataReader._get_lbllistlsZ  3 & &AA  !C ' 'AAASSSSStzARARSSSSrWcjdkr!fdtjD}nLjdkr!fdtjD}n fdtjD}|S)Nr'cjg|]/}jd0S)iArrRrrs rUrVz4StataReader._get_variable_labels..wsC>? T.33C8899rWrcjg|]/}jd0S)Qrrs rUrVz4StataReader._get_variable_labels..{C=> T.33B7788rWcjg|]/}jd0S)r.rrs rUrVz4StataReader._get_variable_labels..rrWr)rvlblists` rUr|z StataReader._get_variable_labelsus  3 & &CHCTCTGG !C ' 'BG BSBSGGBG BSBSGrWch|jdkr|S|S)Nr')r(r;r9r_s rUrazStataReader._get_nobss4  3 & &$$&& &$$&& &rWrFc|jdkrA|}||j|S|jdkrA|}||j|S|jdkr-||jdS||jdS)Nr'rOrrr.)r(r5rrrr,rstrlens rUrczStataReader._get_data_labels  3 & &&&((F<< 1 6 6v > >?? ?  !S ( (__&&F<< 1 6 6v > >?? ?  !C ' '<< 1 6 6r : :;; ;<< 1 6 6r : :;; ;rWc|jdkrA|}|j|dS|jdkrA|}||j|S|jdkr-||jdSt )Nr'rrOr)r(r,rrdecoderrurs rUrezStataReader._get_time_stamps  3 & &__&&F$))&1188AA A  !S ( (__&&F<< 1 6 6v > >?? ?  !C ' '<< 1 6 6r : :;; ;,, rWc|jdkr2|jd|jd|jzzdzdzS|jdkr|dzSt )NrOrrr')r(rrrkr`rArur_s rUrlz%StataReader._get_seek_variable_labelssv  3 & &   " "1 % % %/2 ?CbH2M M  !S ( (##%%* *,, rWrLct|d_jdvr-ttjdkrdnd__j d _ ___jdkr*dj j D}nj j }t'j|t&j }g}|D]D}|jvr!|j|,||d z E fd |D_nE#t$r8}d d |D}td|d|d}~wwxYw fd|D_nE#t$r8}d d|D}td|d|d}~wwxYwjdkr&fdt7j D_n%fdt7j D_j dzdd__ !_"#_$jdkrk } jdkr%} n&} | dkrnj | jj '_(dS)Nr)rrrorrsrQrBrTrUrc,g|]}t|SrC)rjrRr1s rUrVz0StataReader._read_old_header..sJJJ!s1vvJJJrWrc*g|]}j|SrC)rrRrrs rUrVz0StataReader._read_old_header..s CCCCT]3/CCCrW,c,g|]}t|SrCrFrRrs rUrVz0StataReader._read_old_header..s%>%>%>c!ff%>%>%>rWrrc*g|]}j|SrC)rrs rUrVz0StataReader._read_old_header..s EEEcdnS1EEErWc,g|]}t|SrCrrs rUrVz0StataReader._read_old_header..s&?&?&?!s1vv&?&?&?rWzcannot convert stata dtypes [cjg|]/}jd0S)rrrs rUrVz0StataReader._read_old_header..sC=> T.33B7788rWcjg|]/}jd0S)r\rrs rUrVz0StataReader._read_old_header..sC<= T.33A6677rWr^r))rjr(rur_rNr)r,r4 _filetyperrr5r`rarbrcrdrerfr frombufferrrr%rrjoinrsr5rvrGrwrxryrzr{r|r}r?r=tellrn) rrLrbuftyplistbtpr invalid_typesinvalid_dtypes data_typedata_lens ` rUrKzStataReader._read_old_headers(":a=11  'J J J^224;O2PPQQ Q !%!2!2c!9!9##s** q!!!&&(( ^^%% //11//11  # % %JJt'8'='=dj'I'IJJJGG#((44C}S999HG - -...NN4#8#<====NN28,,,, WCCCC7CCCDMM W W WHH%>%>g%>%>%>??MLMLLLMMSV V W YEEEEWEEEDNN Y Y Y XX&?&?w&?&?&?@@NN^NNNOOUX X Y  # % %BG BSBSDMMAFtzARARDM..tzA~>>ssC ))++ ))++ $ 9 9 ; ;  # % % 1 OO-- '#--#//11HH#//11H>>!&&x000 1#/4466s0G00 H2:3H--H26I J 3JJ rlcj|j|jSg}t|jD]o\}}||jvrDt t |}|d||j|j|fR|d|d|fptj ||_|jS)z"Map between numpy and state dtypesNsr|) rrrrrr rFr%r4rr)rdtypesr-rs rUrzStataReader._setup_dtypes ; ";  .. 4 4FAsd)))3nn w1ww4?(VD,,A %;;&w/A77#s**!&&q)))C! *D#'rWc|j|jddi|_ |jddkrdS|jdkr|}n|jd}|jdkrd nd}|jd kr|d ||d d|z z}n|d ||d |zdz}tj d |d }| }| }|j|}|dkr#|d d |j }nt|}||jt|<S)N0rTrsGSOrOrr'rrUrrrr^)rrtroGSOrr(r;r4rrr0r9rrrF)rv_orv_sizerlengthva decoded_vas rU _read_strlszStataReader._read_strlsWs t/0009 , %%a((F22#s**''))',,R00"2c99q?c))ah-#a2;.?*@@CCah-#q6znn*==CmC--a0""$$C&&((F"''//Bczz"X__T^<< !WW !+DHSXX 3 ,rWr$cFd|_||jS)NTnrows)rrrr_s rU__next__zStataReader.__next__vs #yyty///rWsizec@||j}||S)a Reads lines from Stata file and returns as dataframe Parameters ---------- size : int, defaults to None Number of lines to read. 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Returns ------- DataFrame Nr)rr)rrs rU get_chunkzStataReader.get_chunkzs$ <?Dyyty$$$rWr bool | Nonec  |||j}||j}||j}||j}||j}||j}||j}||j}|jdkr|dkrd|_ d|_ t|j } t| jD]U\} } |j| } t!| t"jr)| jdkr| | | | | <V||| |} | S|jdkr"|jsd|_ ||jJ|j} |j|jz | jz}|| jz}t9||}|dkr|r|t<|j| jz}|j |j!|zt9||j|jz }t#j"|j#|| |}|xj|z c_|j|jkrd|_ d|_ |j$|j%kr>|&'|j(}|r|tS|dkrt|j } n-tj*|} tW|j | _|"tY|j|z |j| _-||| |} t]| |j/D]=\} }t!|t`r#| | 1|j2| | <>|3| } dt|jD}t#jth}|D]a}| j5dd|fj} | ||j|fvr8| 6|| j5dd|f| b|7| |} |rmt|j8D]X\} tsfdttDr3| 6| tw| j5dd| fY|r-|jd kr"|<| |j=|j>|} |sEg}d }| D]} | | j} | t#jt"j?t#jt"j@fvr!t#jt"jA} d}n{| t#jt"jBt#jt"jCt#jt"jDfvr t#jt"jE} d}|F| | | | f|r!tjGt|} |(| I| J|} | S) NrT)rr|rOrcg|] \}}|| SrcrC)rRr-dtyps rUrVz$StataReader.read..s!WWWgadFVFVFVFVrWc3BK|]}|VdSrc)r)rRdate_fmtrEs rU z#StataReader.read..s/NNHs~~h//NNNNNNrWrF)Krrrrrrrrrbrrr$rvrrrsrrrcharr_do_select_columnsr(rrrrrrZr StopIterationrrtrnrrr4r byteswapr newbyteorderr# from_recordsr%r&rOr\rrrjrr _insert_strlsrilocisetitem_do_convert_missingryr _date_formatsr_do_convert_categoricalsrr{float16rrrrrrr% from_dictr set_indexpop)rrrrrrrrrrr-rdtr max_read_lenread_lenr: read_linesraw_datar valid_dtypes object_typeidx retyped_dataconvertrEs @rUrzStataReader.reads    /M  '#'#=  ""3O  ""3O ?mG  %!%!9   I =JE J!OO!*.D '"DOT]333D#DL11 9 93^A&b"(++9w#~~$(I$4$4R$8$8S "..tW==K  C ' '$2I '*.D '      {&&&  T%55G 5>)x.. q==$ *''))) !EN2 t2V;<<< T-= =>> =   " "8 , ,E    J&  tz ) )*.D '"DO ?d4 4 4((**//0K0K0M0MNNH  &  # # % % % x==A  T]333DD)(33D //DL  # :-t/?DJ  **499DD$-00 : :HC#s## : IOODL99S !!$''XW4>)B)BWWW hv&&  D DCIaaaf%+E[$.*=>>> c49QQQV#4#;#;E#B#BCCC''o>>  #DM22  3NNNN NNNNNMM>tyAPSTT  D$83$>$>00d,dm=OD ?LG D DS RXbj1128BJ3G3GHHHHRZ00E"GGHRW%%HRX&&HRX&& HRX..E"G##S$s)*:*:5*A*A$BCCCC ? *4 +=+=>>  >>$((9"5"566D rWrci}tt|jD]}|j|}||jvrt t |}|j|\}}|jdd|f}|j} | |k| |kz} | sy|rtj tj | d} tj || d\} } t|t}t!| D]*\}}t#|}| | |k}||j|<+nx|j}|tjtjfvr tj}t||}|jjds|}tj|j| <|||<|r0|D]\}}||||S)NrT)return_inverser WRITEABLE)r5r#rrrrr rFrrrrnonzeroasarrayuniquer'rrrrrrflagsrnanrKr)rrr replacementsr-rEnminnmaxseriessvalsmissing missing_locumissing umissing_loc replacementjumrrrr rks rUrzStataReader._do_convert_missing#s s4<(())% *% *A-"C$***sC..C)#.JD$Yqqq!t_FNEt| 5G;;==  6 jG)<)<==a@ )+6'?SW)X)X)X&,$V6::: &x00::EAr$5b$9$9M%la&78C,9K$S)) :  RZ 888JE$V5999 "*0=5#."2"2"4"4K02v #G,)LOO  **0022 * * U c5)))) rWctdrtjdkr|StjD]=\}}|dkr ||fd|jdd|fD>|S)NrrrcDg|]}jt|SrC)rrF)rRkrs rUrVz-StataReader._insert_strls..Xs&HHH1dhs1vv.HHHrW)r r#rrrrrr)rrr-rs` rUrzStataReader._insert_strlsQstU## s48}}'9'9K .. J JFAsczz MM!HHHH !!!Q$HHH I I I I rW Sequence[str]c|jsXt|}t|t|krtd||j}|r4dt|}td|g}g}g}g} |D]} |j| } | |j | | |j | | |j | | |j | ||_ ||_ ||_ | |_ d|_||S)Nz"columns contains duplicate entriesz, z>&--bl;;;;&--h7777 8"&biikk!2!2J3 (99*EEHH!333 777DDFFB$("q&)9$:$:M- -0H0HHG       C%S//s2!3$$HDJUKKK "))3 *;<<<<"))3S *:;;;;011>>> sE G&A2GGc8||jS)a Return data label of Stata file. Examples -------- >>> df = pd.DataFrame([(1,)], columns=["variable"]) >>> time_stamp = pd.Timestamp(2000, 2, 29, 14, 21) >>> data_label = "This is a data file." >>> path = "/My_path/filename.dta" >>> df.to_stata(path, time_stamp=time_stamp, # doctest: +SKIP ... data_label=data_label, # doctest: +SKIP ... version=None) # doctest: +SKIP >>> with pd.io.stata.StataReader(path) as reader: # doctest: +SKIP ... print(reader.data_label) # doctest: +SKIP This is a data file. )rrdr_s rU data_labelzStataReader.data_labels$ rWc8||jS)z2 Return time stamp of Stata file. )rrfr_s rU time_stampzStataReader.time_stamps rWdict[str, str]cx|tt|j|jS)a Return a dict associating each variable name with corresponding label. Returns ------- dict Examples -------- >>> df = pd.DataFrame([[1, 2], [3, 4]], columns=["col_1", "col_2"]) >>> time_stamp = pd.Timestamp(2000, 2, 29, 14, 21) >>> path = "/My_path/filename.dta" >>> variable_labels = {"col_1": "This is an example"} >>> df.to_stata(path, time_stamp=time_stamp, # doctest: +SKIP ... variable_labels=variable_labels, version=None) # doctest: +SKIP >>> with pd.io.stata.StataReader(path) as reader: # doctest: +SKIP ... print(reader.variable_labels()) # doctest: +SKIP {'index': '', 'col_1': 'This is an example', 'col_2': ''} >>> pd.read_stata(path) # doctest: +SKIP index col_1 col_2 0 0 1 2 1 1 3 4 )rrr\rvr}r_s rUvariable_labelszStataReader.variable_labelss30 C t'<==>>>rWcF|js||jS)aX Return a nested dict associating each variable name to its value and label. Returns ------- dict Examples -------- >>> df = pd.DataFrame([[1, 2], [3, 4]], columns=["col_1", "col_2"]) >>> time_stamp = pd.Timestamp(2000, 2, 29, 14, 21) >>> path = "/My_path/filename.dta" >>> value_labels = {"col_1": {3: "x"}} >>> df.to_stata(path, time_stamp=time_stamp, # doctest: +SKIP ... value_labels=value_labels, version=None) # doctest: +SKIP >>> with pd.io.stata.StataReader(path) as reader: # doctest: +SKIP ... print(reader.value_labels()) # doctest: +SKIP {'col_1': {3: 'x'}} >>> pd.read_stata(path) # doctest: +SKIP index col_1 col_2 0 0 1 2 1 1 x 4 )rrrr_s rUrzStataReader.value_labelss*0& &  # # % % %%%rW) TTNFTNTNrN)rrrrrrrrrrrrrrrrrrrr.r7rrGr r>)rGr1)rrrrr r!rGr )rGrj)rGr*)rDrjrGrE)r~rjrGr)rGrrp)rLr*rGr )rGrl)rr*rGrF)rGr$rc)rrrGr$)NNNNNNNN)rrrrrrrrrrrrrrrrrGr$)rr$rrrGr$rr$rGr$)rr$rr&rGr$) rr$r0r1r/r&rrrGr$)rGrG)rGr1)6r?r@rA_stata_reader_docrBrqrrr rr#rr)r,r0r5r9r;r=r?rArCrGrrJrqrurxrzr|rarcrerlrKrrrrrrr_read_method_docrrrrrrvrDrFrIr __classcell__r s@rUrr`sqG #%) $ % $(,#' $*115/@/@/@/@/@/@/@b> $%%%%@@@@@@@@RRRRRRRRRRRRRRRRRRRRRRRR@@@@    ....5<5<5<50000%%%%%"X!%),0 $'+'+(,*.UUUU Un,,,,\@LLLL\   X (   X ????6&&&&&&&&rWrTFr) rrrrrrrriteratorrr7rrrrrrrrrrrrrrPrr.rDataFrame | StataReaderc t|||||||||| |  } | s|r| S| 5| cdddS#1swxYwYdS)N) rrrrrrrrr7r)rr) r6rrrrrrrrrPrr7readers rU read_statarTs #1''-'   F9 {{}}sAA A endiannessc|dvrdS|dvrdStd|d)N)rUlittlerU)rTbigrTz Endianness r)lowerru)rUs rUrrDsT_,,s     | + +sBzBBBCCCrWrr rrjct|tr|d|t|z zzS|d|t|z zzS)zQ Take a char string and pads it with null bytes until it's length chars. r,)rr*r#rrs rUr4r4MsL$5g#d))!3444 &FSYY./ //rWrlcl|dvrtjtjStd|d)zK Convert from one of the stata date formats to a type in TYPE_MAP. )r~r8rr:rr<rr=rr>rr?rr@rz not implemented)rrrNotImplementedError)rEs rU_convert_datetime_to_stata_typer_VsD  x ###!"AC"A"A"ABBBrWrvarlistlist[Hashable]cRi}|D]}||dsd||z||<||vr1|||||i`t|tst d||||i|S)N%z0convert_dates key must be a column or an integer)rupdaterOrrjru)rr`new_dictrIs rU_maybe_convert_to_int_keysrfosH77S!,,S11 :!$}S'9!9M#  '>> OOW]]3//s1CD E E E Ec3'' U !STTT OOS-"45 6 6 6 6 OrWrr;c|jtjur1tt |j}t |dS|jtjurdS|jtjurdS|jtj urdS|jtj urdS|jtj urdStd|d) a Convert dtype types to stata types. Returns the byte of the given ordinal. See TYPE_MAP and comments for an explanation. This is also explained in the dta spec. 1 - 244 are strings of this length Pandas Stata 251 - for int8 byte 252 - for int16 int 253 - for int32 long 254 - for float32 float 255 - for double double If there are dates to convert, then dtype will already have the correct type inserted. rBrrrrr~ Data type  not supported. rgrobject_rrrrYrrrrrr^)rr;rs rU_dtype_to_stata_typerl}s" zRZ( fn(E(EFF8Q rz ! !s rz ! !s rx  s rx  s rw  s!"Eu"E"E"EFFFrWr dta_version force_strlc |dkrd}nd}|rdS|jtjur~tt |j}||kr4|dkrdSt t|j dtt|dzdzS|tj krdS|tj krd S|tjkrd S|tjtjfvrd St#d |d )a Map numpy dtype to stata's default format for this type. Not terribly important since users can change this in Stata. Semantics are object -> "%DDs" where DD is the length of the string. If not a string, raise ValueError float64 -> "%10.0g" float32 -> "%9.0g" int64 -> "%9.0g" int32 -> "%12.0g" int16 -> "%8.0g" int8 -> "%8.0g" strl -> "%9s" rOrz%9srcrBrz%10.0gz%9.0gz%12.0gz%8.0grhri)rgrrkrrrrurrNrrFrYrrrrrr^)rr;rmrn max_str_lenrs rU_dtype_to_default_stata_fmtrrs&S   5 zRZ' fn(E(EFF k ! !c!!u !>!E!Efk!R!RSSSSXq))***S00 "*  x "*  w "(  x 27BH% % %w!"Eu"E"E"EFFFrWcompression_optionsfname)r7rsc^eZdZUdZdZdZded< dKdd dLfd ZdMd#ZdNd&Z dOd(Z dPd)Z dPd*Z dQd+Z dRd-ZdPd.ZdSd1ZdTd2ZdQd3ZdQd4ZdQd5ZdQd6ZdQd7ZdQd8ZdQd9ZdQd:ZdQd;Z dUdVd<ZdQd=ZdQd>ZdQd?ZdQd@ZdQdAZ dQdBZ!dPdCZ"dWdEZ#dXdGZ$e%dYdIZ&dZdJZ'xZ(S)[ StataWriterar A class for writing Stata binary dta files 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. {compression_options} .. versionchanged:: 1.4.0 Zstandard support. {storage_options} value_labels : dict of dicts Dictionary containing columns as keys and dictionaries of column value to labels as values. The combined length of all labels for a single variable must be 32,000 characters or smaller. .. versionadded:: 1.4.0 Returns ------- writer : StataWriter instance The StataWriter 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 * 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 -------- >>> data = pd.DataFrame([[1.0, 1]], columns=['a', 'b']) >>> writer = StataWriter('./data_file.dta', data) >>> writer.write_file() Directly write a zip file >>> compression = {{"method": "zip", "archive_name": "data_file.dta"}} >>> writer = StataWriter('./data_file.zip', data, compression=compression) >>> writer.write_file() Save a DataFrame with dates >>> from datetime import datetime >>> data = pd.DataFrame([[datetime(2000,1,1)]], columns=['date']) >>> writer = StataWriter('./date_data_file.dta', data, {{'date' : 'tw'}}) >>> writer.write_file() rpr r rNTrrrtFilePath | WriteBuffer[bytes]rr$rdict[Hashable, str] | None write_indexrr)rrFdatetime | NonerDrIrr.r7rr'dict[Hashable, dict[float, str]] | NonerGr c t||_|in||_||_||_||_||_| |_g|_ tj gt|_ | |_d|_i|_||| |_| t&j}t+||_||_tjtjtjd|_dS)Nr)rrr~)rrrr _write_indexrfrdr}_non_cat_value_labels _value_labelsrr r_has_value_labelsr _output_file_converted_names_prepare_pandasr7rr)rr4_fnamerrrtype_converters) rrtrrrzr)rFrDrIrr7rr s rUrzStataWriter.__init__$ s  $1$9bb}'%% /%1"46!#"D!9!9!9'.257 T""".   I))44 %'XBH27KKrWto_writerFct|jj||jdS)zS Helper to call encode before writing to file for Python 3 compat. N)rrr2r$r)rrs rU_writezStataWriter._writeJ s1 !!(//$."A"ABBBBBrWrkr*cD|jj|dS)z? Helper to assert file is open before writing. N)rrr2r]s rU _write_byteszStataWriter._write_bytesP s# !!%(((((rWlist[StataNonCatValueLabel]cg}|j|S|jD]\}}||jvr|j|}n,||jvrt |}nt d|dt ||jstd|dt|||j }| ||S)zc Check for value labels provided for non-categorical columns. Value labels NzCan't create value labels for z!, it wasn't found in the dataset.z6, value labels can only be applied to numeric columns.) rrKrrrFrrrrurErr%)rrnon_cat_value_labelsrlabelscolnamesvls rU_prepare_non_cat_value_labelsz)StataWriter._prepare_non_cat_value_labelsV s=?  % -' '#9??AA - -OGV$////8DL((g,,,W,,, $DM$788 !>W>>>(HHC ' ' , , , ,##rWc>d|jD}t|s|S|xjtj|zc_t j}g}t||D]\}}|rst|||j }|j |||j j j}|tjkrt!d||j j j} | ||kr|tjkrtjtj}nM|tjkrtjtj}ntjtj}tj| |} ||| | dk<| || f|| |||ft1jt5|S)z Check for categorical columns, retain categorical information for Stata file and convert categorical data to int c8g|]}t|tSrC)rr)rRrs rUrVz5StataWriter._prepare_categoricals..| s#OOO%*U$455OOOrW)r zCIt is not possible to export int64-based categorical data to Stata.rr^)rrrrr rror\rrrr%rcodesrrrurrrYrrrrr$rr) rris_catrodata_formattedr col_is_catrrrws rU_prepare_categoricalsz!StataWriter._prepare_categoricalsw s PO4;OOO6{{ K "(6"2"22!2!I"400 8 8OC 8%d3i$.III"))#...S +1BH$$$Ac,499;;::<<#9#9%#@#@@@'' " 2 2"(** " 2 2 " 4 4XfE:::F(>'=e'D'Dv|$%%sFm4444%%sDI&67777"4#7#7888rWc|D]r}||j}|tjtjfvrI|tjkr|jd}n |jd}|||||<s|S)z Checks floating point data columns for nans, and replaces these with the generic Stata for missing value (.) rrd)rrrrrMr)rrr1rr s rU _replace_nanszStataWriter._replace_nans sz  6 6AGMERZ000BJ&&"&"5c":KK"&"5c":Kq'..55Q rWcdS)zNo-op, forward compatibilityNrCr_s rU_update_strl_nameszStataWriter._update_strl_names rWrc|D]B}|dks|dkr4|dks|dkr(|dks|dkr|dkr||d}C|S)a Validate variable names for Stata export. Parameters ---------- name : str Variable name Returns ------- str The validated name with invalid characters replaced with underscores. Notes ----- Stata 114 and 117 support ascii characters in a-z, A-Z, 0-9 and _. AZazr9r)replacerrr1s rU_validate_variable_namez#StataWriter._validate_variable_name sh( , ,ASAGGWWCWWCHH||As++ rWci}t|j}|dd}d}t|D]\}}|}t|tst |}||}||jvrd|z}d|dcxkrdkrnnd|z}|dtt|d}||ksv| |dkrXdt |z|z}|dtt|d}|dz }| |dkX|||<|||<t||_|j r9t||D](\} } | | kr|j | |j | <|j | =)|rg} | D]!\}}|d|} | | "td | } t%j| t(t+ ||_||S) a Checks column names to ensure that they are valid Stata column names. This includes checks for: * Non-string names * Stata keywords * Variables that start with numbers * Variables with names that are too long When an illegal variable name is detected, it is converted, and if dates are exported, the variable name is propagated to the date conversion dictionary Nrrrrr.rBz -> z r)rrrrrFrrrZr#rDr%rr\rKr%rrNrrrrrrr)rrconverted_namesroriginal_columnsduplicate_var_idr!r orig_namer1oconversion_warningrrs rU_check_column_nameszStataWriter._check_column_names s02t|$$"111: ))  GAtIdC(( !4yy//55Dt***Tzd1g$$$$$$$$$Tz,#c$ii,,,-D9$$mmD))A--%5!6!66=D 4#c$ii"4"4 45D$)$ mmD))A-- .2 *GAJJW~~    /G%566 / /166-1-@-CD'*+A.  !# #2#8#8#:#: / / 4"22D22"))#....!((7I)J)JKKB M!+--     !0 !!! rWrr'c"g|_g|_|D]k\}}|jt ||j||jt ||j|ldSrc)r.rrKr%rrrrl)rrrrs rU_set_formats_and_typesz"StataWriter._set_formats_and_types s"$ "$  ,,.. M MJC L   ;E49S> R R S S S L   4UDIcN K K L L L L M MrWc|}|jr+|}t|tr|}||}t |}||}tj d|j d|_ | |}d|D}|j |}|xj |zc_ |j|||}|j \|_|_||_|j |_|j}|D]6}||jvr t3j||jdr d|j|<7t9|j|j|_|jD]8}t;|j|} tj| |j|<9|| ||j4|jD].}t|tBr|j||j"|<-dSdS)NFrBcg|] }|j SrC)r)rRrs rUrVz/StataWriter._prepare_pandas..> sGGG33;GGGrWrr~)#rr~ reset_indexrr$rrrrrepeatrrrrr5rextendrnobsnvarrtolistr`rrrrrrfr_r_encode_stringsrrjr.) rrtemprnon_cat_columnshas_non_cat_val_labelsrrrInew_types rUrzStataWriter._prepare_pandas# syyy{{   ##%%D$ ** ''--$D))!!$''"$5$*Q-!@!@ $AA$GGGG2FGGG!%!2!2?!C!C "88 !!"6777))$//#z 49 |**,,  0 0Cd)))tCy44 0+/#C(8    & 2 2C6t7J37OPPH!x11FK    ##F+++   ** A Ac3''A(,(;C(@DL% + * A ArWc|j}t|dg}t|jD]\}}||vs||vr|j|}|j}|jt jurt|d}|dks-t|dks|j }td|d|j|j |j}tt!|j|jkr ||j|<dS) z Encode strings in dta-specific encoding Do not encode columns marked for date conversion or for strL conversion. The strL converter independently handles conversion and also accepts empty string arrays. _convert_strlTrr`rzColumn `a` cannot be exported. Only string-like object arrays containing all strings or a mix of strings and None can be exported. Object arrays containing only null values are prohibited. Other object types cannot be exported and must first be converted to one of the supported types.N)rr[rrrrgrrkrr#rrurFr$rrrr_max_string_length) rr convert_strlr-rr;rinferred_dtypeencodeds rUrzStataWriter._encode_stringse s/+ t_b99  ** - -FAsM!!SL%8%8Ys^FLEzRZ''!,VD!A!A!A'833F q8H8H +C$ )C.,33DNCC)w)G)GHH.//&-DIcN3 - -rWc t|jd|jd|j5|_|jjdS|jjtc|_|j_|jj |jj | |j |j ||||||||||}|||||||n#t:$r}|jt?|jt@tBj"frtBj#$|jr\ tCj%|jnA#tL$r4tOj(d|jdtRtU YnwxYw|d}~wwxYw ddddS#1swxYwYdS) a Export DataFrame object to Stata dta format. Examples -------- >>> df = pd.DataFrame({"fully_labelled": [1, 2, 3, 3, 1], ... "partially_labelled": [1.0, 2.0, np.nan, 9.0, np.nan], ... "Y": [7, 7, 9, 8, 10], ... "Z": pd.Categorical(["j", "k", "l", "k", "j"]), ... }) >>> path = "/My_path/filename.dta" >>> labels = {"fully_labelled": {1: "one", 2: "two", 3: "three"}, ... "partially_labelled": {1.0: "one", 2.0: "two"}, ... } >>> writer = pd.io.stata.StataWriter(path, ... df, ... value_labels=labels) # doctest: +SKIP >>> writer.write_file() # doctest: +SKIP >>> df = pd.read_stata(path) # doctest: +SKIP >>> df # doctest: +SKIP index fully_labelled partially_labeled Y Z 0 0 one one 7 j 1 1 two two 7 k 2 2 three NaN 9 l 3 3 three 9.0 8 k 4 4 one NaN 10 j wbF)rrr7methodN)rDrFz!This save was not successful but z. could not be deleted. This file is not valid.r)+r)rrr7rrrrrcreated_handlesr% _write_headerrdrf _write_map_write_variable_types_write_varnames_write_sortlist_write_formats_write_value_label_names_write_variable_labels_write_expansion_fields_write_characteristics _prepare_data _write_data _write_strls_write_value_labels_write_file_close_tag_close ExceptionrrrFosPathLikepathisfileunlinkOSErrorrrrr)rrecordsexcs rU write_filezStataWriter.write_file s%8 K ) 0    /  \|'1=:>9Lgii6!4<#6 ,33DL4GHHH" ""#/D> 27>>KDD  $+...." B BBB+'7'9'9   A/ / / / / / / / / / / / / / / / / / s\A+KE"G32K3 K=A#J>!I;:J>;;J96J>8J99J>>KKKKc|jrt|jjtsJ|jj|jc}|j_|jj|dSdS)z Close the file if it was created by the writer. If a buffer or file-like object was passed in, for example a GzipFile, then leave this file open for the caller to close. N)rrrrrr2r6)rr7s rUrzStataWriter._close sp   (dl17;; ; ;;'+|':D||t|dd d |tj }n$t|tstd gd}dt|D}|d||jz|dz}|||dS)NrrrrTr[rrr-rrP"time_stamp should be datetime type JanFebMarAprMayJunJulAugSepOctNovDecc i|] \}}|dz| SrQrCrRr-r^s rU z-StataWriter._write_header..( "GGGEAuGGGrW%d %Y %H:%M)r4rrr3rrr_null_terminate_bytesr4rnowrrurstrftimer^)rrDrFr)months month_lookuptss rUrzStataWriter._write_header s  O  &+c3//000 I$/96::: F F &+i#otyAA"1"EFFF &+i#otyAA"1"EFFF     d88B9K9KLL M M M M   **:j"or+J+JKK     !JJJ11 CABB B    HGYv5F5FGGG    & &:+, -!!+.. / $44R8899999rWcj|jD]*}|tjd|+dS)Nr/)rrrr3)rrs rUrz!StataWriter._write_variable_types0 s@< 5 5C   fk#s33 4 4 4 4 5 5rWc|jD]D}||}t|ddd}||EdS)Nr.r)r`_null_terminate_strr4r)rrs rUrzStataWriter._write_varnames4 s^L  D++D11Dd3B3i,,D KK      rWcftdd|jdzz}||dS)NrrrB)r4rr)rsrtlists rUrzStataWriter._write_sortlist< s4Rdi!m!455 GrWc`|jD]%}|t|d&dS)Nr)r.rr4)rrEs rUrzStataWriter._write_formatsA s<< - -C KK 3++ , , , , - -rWc4t|jD]}|j|rP|j|}||}t |ddd}||_|t dddS)Nr.rr)r5rrr`r r4r)rr-rs rUrz$StataWriter._write_value_label_namesF sty!! 0 0A%a( 0|A//55!$ss)R00 D!!!! Jr2..//// 0 0rWctdd}|j.t|jD]}||dS|jD]}||jvr}|j|}t |dkrtdtd|D}|std|t|d||dS)Nrrr.Variable labels must be 80 characters or fewerc3<K|]}t|dkVdS)N)ordrs rUrz5StataWriter._write_variable_labels..` s,<<A <<<<<S 4<?!!DI""4((?ocm.L.LLoo $ $FAs!*Cd---,....+ 9!. c))"--B ...............HHZsfH==S !C #s  I,,U33S S '@!..t??E#s U&AAAs 8DD D rcT||dSrc)rtobytesrrs rUrzStataWriter._write_data s& '//++,,,,,rWrc|dz }|S)Nr[rC)rs rUr zStataWriter._null_terminate_str s V rWc\|||jSrc)r r$r)rrs rUrz!StataWriter._null_terminate_bytes s&''**11$.AAArW)NTNNNNrN)rtrxrr$rryrzrr)rrFr{rDrrIryrr.r7rrr|rGr )rrFrGr )rkr*rGr )rr$rGrrKr>rrFrGrFrr'rGr )rr$rGr NNrDrrFr{rGr )rGr)rrrGr )rrFrGrF)rrFrGr*))r?r@rArBrrrqrrrrrrrrrrrrrrrrrrrrrrrrrrrrrr staticmethodr rrNrOs@rUrvrvsT LL\-6I6666 59 $&*!%6:*115$LAE$L$L$L$L$L$L$L$LLCCCC )))) $$$$B(9(9(9(9T"++++", "<", "little", or "big". default is `sys.byteorder` Notes ----- Supports creation of the StrL block of a dta file for dta versions 117, 118 and 119. These differ in how the GSO is stored. 118 and 119 store the GSO lookup value as a uint32 and a uint64, while 117 uses two uint32s. 118 and 119 also encode all strings as unicode which is required by the format. 117 uses 'latin-1' a fixed width encoding that extends the 7-bit ascii table with an additional 128 characters. rONdfr$rr&rRrjr)rrGr c8|dvrtd||_||_||_ddi|_| t j}t||_d}d}d|_ |dkr d }d}d |_ n |d krd }nd }ddd|z zz|_ ||_ ||_ dS)NrNz,Only dta versions 117, 118 and 119 supportedrrrr8rrrOrr r'rrrr) ru_dta_verr6r _gso_tablerr)rr4r_o_offet _gso_o_type _gso_v_type)rr6rrRr) gso_v_type gso_o_typeo_sizes rUrzStataStrLWriter.__init__ s / ) )KLL L  v,   I))44    c>>FJ&DNN ^^FFFa1v:./ %%rWrItuple[int, int]c&|\}}||j|zzSrc)r;)rrIrrs rU _convert_keyzStataStrLWriter._convert_key s14=1$$$rW,tuple[dict[str, tuple[int, int]], DataFrame]cN|j}|j}t|j||j}fd|jD}t j|jtj}t| D]o\}\}}t|D]W\} \} } || } | dn| } | | d} | | dz|dzf} | || <| | ||| f<Xpt|jD]\}} |dd|f|| <||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 c>g|]}||fSrCrX)rRrrs rUrVz2StataStrLWriter.generate_table..7 s*GGG3c7==--.GGGrWrNrrB) r:r6rrremptyrrriterrowsgetrC)r gso_tablegso_dfselected col_indexr4rr rowr!rrr"rIr-rs @rUgenerate_tablezStataStrLWriter.generate_table sV:O v~&&$,'GGGG$,GGG xbi888&x'8'8':':;; 4 4MAzS(33 4 4 8C#hKbbSmmC..;q5!a%.C%(IcN!..s33QT  4  -- % %FAsqqq!t*F3KK&  rWrJdict[str, tuple[int, int]]r*c Nt}tdd}tj|jdzd}tj|jdzd}|j|jz}|j|jz}|jdz}|D]\} } | dkr | \} } |||tj|| |tj|| ||t| d} |tj|t| d z|| ||| 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. rasciir/rrr8r8rrB) rr*rr3r4r=r<rKr2r#r6)rrJr7gsogso_typenullv_typeo_typelen_typestrlvorr utf8_strings rU generate_blobzStataStrLWriter.generate_blobI s|:iiE7##;t4c::{4?S0!444#334#33?S(!))  HD"V||DAq IIcNNN IIfk&!,, - - - IIfk&!,, - - - IIh    g..K IIfk(C ,<,d'Z d?d@d(Z dAd)Z dAd*Z dAd+Z dAd,ZdAd-ZdAd.ZdAd/ZdAd0ZdAd1ZdAd2ZdAd3ZdAd4ZdAd5ZdAd6ZdBd7ZdCd:ZxZS)DStataWriter117a A class for writing Stata binary dta files in Stata 13 format (117) 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_options} .. versionchanged:: 1.4.0 Zstandard support. value_labels : dict of dicts Dictionary containing columns as keys and dictionaries of column value to labels as values. The combined length of all labels for a single variable must be 32,000 characters or smaller. .. versionadded:: 1.4.0 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 * 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 -------- >>> data = pd.DataFrame([[1.0, 1, 'a']], columns=['a', 'b', 'c']) >>> writer = pd.io.stata.StataWriter117('./data_file.dta', data) >>> writer.write_file() Directly write a zip file >>> compression = {"method": "zip", "archive_name": "data_file.dta"} >>> writer = pd.io.stata.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 = pd.io.stata.StataWriter117( ... './data_file_with_long_strings.dta', data, convert_strl=['strls']) >>> writer.write_file() rrONTrrwrtrxrr$rryrzrr)rrFr{rDrIrSequence[Hashable] | Nonerr.r7rrr|rGr c  g|_| |j| t||||||||| | |  i|_d|_dS)N)r)rFrDrIrrr7rW)rrrr_map _strl_blob)rrtrrrzr)rFrDrIrrr7rr s rUrzStataWriter117.__init__ s".0  #   % %l 3 3 3     !!+%#+  %' rWr"r1tagrFr*ct|trt|d}td|zdzd|ztd|zdzdzS)zSurround val with rrUrTzrreleaserTMSFLSFr)r'r2r8KrOrNNrrr/r:rrc i|] \}}|dz| SrQrCrs rUrz0StataWriter117._write_header..B rrWrr timestampheader)r4rr*rr2rerF _dta_versionrr3rrr$rr#rrrrurrr^r6)rrDrFr)r7 nvar_type nobs_sizer: encoded_label label_size label_lenrrr stata_tss rUrzStataWriter117._write_header s O  % w77888ii $))E#d&7"8"8'BBINNOOO $))I,6?%MMNNN,33CC  $))FK I(=tyII3OOPPP,33CC  $))FK I(=tyII3OOPPP#-#9 3B3r T^44  -44SS# K J 6M8J8JKK !M1  $))M733444  !JJJ11 CABB B    HGYv5F5FGGG    & &:+, -!!+.. / U2w/// $))Hk22333 $))CLLNNH==>>>>>rWc|js2d|jjddddddddddddd|_|jj|jdt }|jD]2}|tj |j dz|3| | | ddS)z Called twice during file write. The first populates the values in the map with 0s. The second call writes the final map locations when all blocks have been written. r) stata_datamapvariable_typesvarnamessortlistformatsvalue_label_namesrIcharacteristicsrstrlsrstata_data_close end-of-filer{rN)rarrrrtrrwr2rr3r4rrer6)rr7r"s rUrzStataWriter117._write_mapM s y |*//11"#%&#$#$ !$% DI"   5!1222ii9##%% ? ?C IIfk$/C"7== > > > > $))CLLNNE::;;;;;rWc6|dt}|jD]2}|t j|jdz|3||| ddS)Nr|r2) rgrrr2rr3r4rrer6)rr7rs rUrz$StataWriter117._write_variable_typesk s )***ii< ? ?C IIfk$/C"7== > > > > $))CLLNN4DEEFFFFFrWc|dt}|jdkrdnd}|jD]_}||}t |dd|j|dz}||`| | | ddS)Nr}rOr.r0rB) rgrrrr`r r3r$rr2rrer6)rr7vn_lenrs rUrzStataWriter117._write_varnamesr s $$$ii(C//SL  D++D11D!$ss)"2"24>"B"BFQJOOD IIdOOOO $))CLLNNJ??@@@@@rWc|d|jdkrdnd}||d|z|jdzzddS)Nr~rPrrr,rB)rgrrrrer)r sort_sizes rUrzStataWriter117._write_sortlist} sd $$$*S00AAa  $))Gi$749q=$I:VVWWWWWrWcj|dt}|jdkrdnd}|jD]=}|t ||j|>|| | ddS)NrrOrr) rgrrrr.r2r3r$rrrer6)rr7fmt_lenrEs rUrzStataWriter117._write_formats s ###ii)S00""b< K KC IInSZZ%?%?II J J J J $))CLLNNI>>?????rWc|dt}|jdkrdnd}t|jD]{}d}|j|r |j|}||}t|dd |j |dz}| ||| | |ddS)NrrOr.r0rrB)rgrrrr5rrr`r r3r$rr2rrer6)rr7vl_lenr-r encoded_names rUrz'StataWriter117._write_value_label_names s ,---ii(C//Sty!! $ $AD%a( '|A++D11D)$ss)*:*:4>*J*JFUVJWWL IIl # # # # $))CLLNN4GHHIIIIIrWcn|dt}|jdkrdnd}td|dz}|jit |jD]}|||| | ddS|j D]}||jvr|j|}t|dkrtd ||j}n*#t $r}td|j|d}~wwxYw|t||dz|||| | ddS) NrIrOri@rrBrzDVariable labels must contain only characters that can be encoded in )rgrrrr3r}r5rr2rrer6rr#rur$rUnicodeEncodeError) rr7rrrrr:rrs rUrz%StataWriter117._write_variable_labels s *+++ii(C//Sr6A:..  (49%% ! ! %      dii 8IJJ K K K F9 ! !Cd+++-c2u::??$%UVVV#ll4>::GG)$>-1^>>  .&1*==>>>> %     $))CLLNN4EFFGGGGGs8D D:D55D:c|d||dddS)NrrW)rgrrer_s rUrz%StataWriter117._write_characteristics s@ *+++ $))C):;;<<<<s)rgrr&r's rUrzStataWriter117._write_data sb     )$$$ '//++,,, *%%%%%rWc|d|||jddS)Nr)rgrrerbr_s rUrzStataWriter117._write_strls s@ !!! $))DOW==>>>>>rWcdS)zNo-op in dta 117+NrCr_s rUrz&StataWriter117._write_expansion_fields rrWc`|dt}|jD]G}||j}||d}||H|||ddS)Nrlbl) rgrrr<r4rer2rr6)rr7r'labs rUrz"StataWriter117._write_value_labels s (((ii$  B))$/::C))C''C IIcNNNN $))CLLNNNCCDDDDDrWc|d|tdd|ddS)Nrz rr)rgrr*r_s rUrz$StataWriter117._write_file_close_tag sO +,,, %88999 '''''rWc|jD]2\}}||jvr$|j|}||j|<3dS)z Update column names for conversion to strl if they might have been changed to comply with Stata naming rules N)rrKrrO)rorignewr s rUrz!StataWriter117._update_strl_names sb .4466 . .ID#t)))(..t44*-"3' . .rWcfdt|D}|rJt||j}|\}}|}||_|S)zg Convert columns to StrLs if either very large or in the convert_strl variable cNg|]!\}}j|dks |jv|"S)r)rr)rRr-rrs rUrVz1StataWriter117._convert_strls.. sE   3|A%''3$2D+D+D +D+D+DrWrQ)rr5rrrOr\rb)rr convert_colssswtabnew_datas` rUrzStataWriter117._convert_strls s     #D//    5!$ d>OPPPC..00MCD!//44DO rWrr'cJg|_g|_|D]\}}||jv}t ||j||j|}|j||jt||j||dS)N)rmrn) rr.rKrrrrrrr%r0)rrrrrnrEs rUrz%StataWriter117._set_formats_and_types s   ,,..  JC 22J- # -% C L   $ $ $ L  ( # KK      rW) NTNNNNNrN)rtrxrr$rryrzrr)rrFr{rDrrIryrr_rr.r7rrr|rGr )r"r1rcrFrGr*)rcrFrGr r,r-r>rKr+)r?r@rArBrrrrr.rergrrrrrrrrrrrrrrrrrrNrOs@rUr^r^ sBSSjL 59 $&*!%6:26*115#AE########JXXX\X 4444"&&*8?8?8?8?8?t<<<<<GGGG A A A AXXXX @@@@ J J J JHHHH@====&&&& ????    EEEE(((( . . . .$rWr^cXeZdZUdZdZded< d'ddd(fd#Zd)d&ZxZS)*StataWriterUTF8u Stata binary dta file writing in Stata 15 (118) and 16 (119) formats DTA 118 and 119 format files support unicode string data (both fixed and strL) format. 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. 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_options} .. versionchanged:: 1.4.0 Zstandard support. value_labels : dict of dicts Dictionary containing columns as keys and dictionaries of column value to labels as values. The combined length of all labels for a single variable must be 32,000 characters or smaller. .. versionadded:: 1.4.0 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 * 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() rzLiteral['utf-8']rNTrrwrtrxrr$rryrzrr)rrFr{rDrIrr_rRrrr.r7rrr|rGr c | |jddkrdnd} n9| dvrtd| dkr |jddkrtdt||||||||| | | |  | |_dS) NrBir'rP)r'rPz"version must be either 118 or 119.zKYou must use version 119 for data sets containing more than32,767 variables) rrzr)rFrDrIrrrr7)rrurrrr)rrtrrrzr)rFrDrIrrRrr7rr s rUrzStataWriterUTF8.__init__is" ?!Z]e33ccGG J & &ABB B ^^ 1  5 5#    '#!!+%%#+  $rWrrFc|D]u}t|dkr*|dks|dkr|dks|dkr|dks|dkr|dks dt|cxkrd ksn|d vr||d}v|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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