Mhn%SrSSKJr SSKJr SSKJrJr SSKJr SSK r SSK r SSK r SSK J r JrJrJrJrJr SSKrSSKrSSKJr SS KJr SS KJr SS KJrJrJrJ r SS K!J"r"J#r# SS K$J%r% SSK&J'r' SSK(J)r)J*r*J+r+ SSK,J-r- SSK.J/r/J0r0J1r1J2r2J3r3J4r4J5r5 SSK6J7r7 SSK8J9r9 SSK:J;r; SSKJ?r? SSK@JArA \(a$SSKBJCrCJDrD SSKEJFrF SSK JGrG SSKHJIrIJJrJJKrKJLrLJMrMJNrN SrOSrPSrQSrRS rSS!rTS"\PS#\QS#\RS#\SS#\?S$S%-S#\?S&S'\TS(3rUS)\PS#\QS*3rVS+\PS#\QS#\RS#\?S$S#\?S&S,\TS#3 rW/S-QrX\"S.S/S/5rYS0\ZS1'SaS2jr[SaS3jr\S4r]S0\ZS5'S6r^S0\ZS7'S8r_S0\ZS9'S:r`S0\ZS;'Sjrb"S?S@5rc"SASB\c5rd"SCSD5re"SESF5rf"SGSH\f\R5rh\""\U5SISISSJSISSISSJSKSSL. ScSMjj5riSdSNjrjSeSOjrkSfSPjrlSgSQjrmShSRjrnSiSjSSjjro\#"\?S&\?STSU-SV9"SWSX\f55rpSkSYjrqSlSZjrr"S[S\5rs"S]S^\p5rt"S_S`\t5rug)ma 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_epochc$^^^^^^[RR[RRsmm[R[ SSS5- R m[R[ SSS5- R mTS-S-S-mTS-S-S-mS"UU4SjjnS"UU4SjjnS"UUUU4Sjjn[ R"U5nS nUR5(aS nS URU'UR[ R5nURS 5(a[nUnU"XxS 5n GOURS5(a<[R"S[!5S9 [#U[$S9n U(a[&X'U $URS5(a[nUn U"XzS5n GOAURS5(a([RUS--n US-S-n U"X5n GOURS5(a'[RUS--n US-S-n U"X5n OURS5(a*[RUS--n US-S-S-n U"X5n OURS5(a*[RUS--n US-S-S-n U"X5n OFURS5(a!Un [ R("U5nU"X5n O[+S US!35eU(a[&X'U $)#ac Convert from SIF to datetime. https://www.stata.com/help.cgi?datetime Parameters ---------- dates : Series The Stata Internal Format date to convert to datetime according to fmt fmt : str The format to convert to. Can be, tc, td, tw, tm, tq, th, ty Returns Returns ------- converted : Series The converted dates Examples -------- >>> dates = pd.Series([52]) >>> _stata_elapsed_date_to_datetime_vec(dates , "%tw") 0 1961-01-01 dtype: datetime64[ns] Notes ----- datetime/c - tc milliseconds since 01jan1960 00:00:00.000, assuming 86,400 s/day datetime/C - tC - NOT IMPLEMENTED milliseconds since 01jan1960 00:00:00.000, adjusted for leap seconds date - td days since 01jan1960 (01jan1960 = 0) weekly date - tw weeks since 1960w1 This assumes 52 weeks in a year, then adds 7 * remainder of the weeks. The datetime value is the start of the week in terms of days in the year, not ISO calendar weeks. monthly date - tm months since 1960m1 quarterly date - tq quarters since 1960q1 half-yearly date - th half-years since 1960h1 yearly date - ty years since 0000 rArBic >UR5T:a$UR5T:a[SU-U-SS9$[USS5n[ [ X5VVs/sHup4[ X4S5PM snnUS9$s snnf)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%mformatindexNrBrK)maxminr"getattrr'zipr)yearmonthrKymMAX_YEARMIN_YEARs A/var/www/html/env/lib/python3.13/site-packages/pandas/io/stata.pyconvert_year_month_safeD_stata_elapsed_date_to_datetime_vec..convert_year_month_safe!st 88: TXXZ(%:sTzE1&A AD'40ET9IJ9I8A!,9IJRWX XJsA9 c 6>UR5TS- :a)UR5T:a[USS9[USS9-$[ USS5n[ X5VVs/sH%up4[ USS5[[U5S9-PM' nnn[XRS 9$s snnf) zc Converts year (e.g. 1999) and days since the start of the year to a datetime or datetime64 Series rB%YrIdunitrKNdaysrL) rMrNr"r#rOrPrrintr')rQr`rKrSr\valuerUrVs rWconvert_year_days_safeC_stata_elapsed_date_to_datetime_vec..convert_year_days_safe.s 88:A &488:+@tD1LC4PP PD'40EGJ4GVtqAq!I3q6$:: %- -s,Bc >[USS5nUS:XaVUR5T:dUR5T:a-UVs/sHo@[[ U5S9-PM nn[ XSS9$OjUS:XaYUR5T:dUR5T :a0UVs/sHo@[[ U5S-S9-PM nn[ XSS9$O [ S 5e[U5n[XS 9nX-$s snfs snf) 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. rKNr\r_rLmsrF) microsecondszformat not understoodr]) rOrMrNrrar' ValueErrorr"r#) basedeltasr^rKr\values MAX_DAY_DELTA MAX_MS_DELTA MIN_DAY_DELTA MIN_MS_DELTAs rWconvert_delta_safe?_stata_elapsed_date_to_datetime_vec..convert_delta_safe<s . 3;zz|m+vzz|m/KAGHAA!77Hf220LT\zz|l*fjjl\.ILRLRq93q6D=BBFf22 /J 45 54 f0}Is C-!C2FTg?r8tcrfr9tCz9Encountered %tC format. Leaving in Stata Internal Format. stackleveldtype)r:tdr;r\r\r<tw4r=tm r>tqr?thr@tyz Date fmt  not understood)returnr')r rNrQrMrr`npisnanany_valuesastypeint64 startswithrCwarningswarnrr'objectr ones_likerh)datesfmtrXrcrpbad_locshas_bad_valuesrirf conv_datesr`rQrR quarter_month first_monthrlrmrUrnrorVs @@@@@@rW#_stata_elapsed_date_to_datetime_vecrs\#++Y]]-?-?Hh]]XdAq%99??M]]XdAq%99??M 2%,t3L 2%,t3L Y Y . .2xxHN||~~"% h LL "E ~~m$$ '$7  & & G') E0 #&J  0 1 1'C8   & &%2+- a+D7  & &%2+-q ,T9  & &%1*,a!+ ,TA  & &%1*,a!#,T9  & &ll5) ,T? 9SE9::"  c^^^ URm SmTS- mS#S$UUU 4Sjjjn[U5nURm UR5(aV[R"UR S5(a[ [5URU'O[URU'US;aU"USS9nURS- nGO}US ;a![R"S [5S 9 UnGOVUS ;aU"USS9nURT-nGO8US ;a9U"USSS9nSUR[R- -URS--nOUS;a8U"USS9nSUR[R- -UR-S- nOUS;a;U"USS9nSUR[R- -URS- S--nOzUS;aKU"USS9nSUR[R- -URS:R!["5-nO)US;aU"USS9nURnO[%SUS35e['U[(R*SS9n[,R."SS 5S!nXeU'['UT SS"9$)%a+ Convert from datetime to SIF. https://www.stata.com/help.cgi?datetime Parameters ---------- dates : Series Series or array containing datetime or datetime64[ns] to convert to the Stata Internal Format given by fmt fmt : str The format to convert to. Can be, tc, td, tw, tm, tq, th, ty l"R:rFFc$>0n[R"URS5(GaU(aPU[[5R S5- nUR R[R5S-US'U(dU(a=[U5nURRUS'URRUS'U(afUR R[R5[USSS9R R[R5- nUT -US 'O[US S 9S :XaU(a<UR [- nSU 4S jjn[R "U5n U "U5US'U(a<UR#S5n U R S-US'U R USS-- US'U(a&SSjn [R "U 5n U "U5US 'O [%S5e['UTS9$)NMnsrFdeltarQrRr[rIr`Fskipnarc\>TUR-SUR--UR-$)Ni@B)r`secondsrg)x US_PER_DAYs rWfC_datetime_to_stata_elapsed_vec..parse_dates_safe..fs)%.1991DDq~~UUrc:SUR-UR-$)NrH)rQrRrs rWJ_datetime_to_stata_elapsed_vec..parse_dates_safe..s3.parse_dates_safe..gs A 66<<.parse_dates_safes  ??5;; , ,"Y{%;%C%CD%II '//44RXX>$F' t*51 &,,11& '--33' "]]//9KfId='$$rxx.) '*4& u - ; 3VLLOuX' "[[)IJ &..#5& '//!F)c/A' =LLOeH& 7  %((rrrrT)rrtz'Stata Internal Format tC not supported.rv)r:rzr{)rQr`r}r~r)rQrrBrrrrrrrFormat z! is not a known Stata date format)rycopy I,,RXX6 bhh xy}}&$)--/F*B I,,RXX6 bhh  :-$)--/[2P I,,RXX6  I,,RZZ8 9==?e+ty}}(/J+227IFB rzz2::. .xx "&&(( cU#EEIMMOE "u': I,,RZZ8 "**$&$!#& ?!!,@@AUAUV.6*+IJ   !') KrcF\rSrSrSrSS SjjrS SjrS SjrSrg) StataValueLabeliz 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. cUS;a [S5eURUlX lURR n[ U5UlUR5 g)Nlatin-1utf-8%Only latin-1 and utf-8 are supported.) rhrlabname _encodingcat categories enumerate value_labels_prepare_value_labels)selfcatarrayencodingrs rW__init__StataValueLabel.__init__sQ / /DE E}} !\\,, %j1 ""$rcJSUl/UlSUl[R"/[R S9Ul[R"/[R S9UlSUl/n/nURGHnUSn[U[5(dJ[U5n[R"[RUR 5["[%5S9 UR'UR(5nUR+UR5 U=R[U5S-- slUR+US5 URR+U5 U=RS- slGM URS:a [-S5e[R"U[R S9Ul[R"U[R S9UlSSUR--SUR--UR-Ulg ) zEncode value labels.rrxrBrvi}zaStata value labels for a single variable must have a combined length less than 32,000 characters.rN)text_lentxtnrarrayroffvallenrrstrrrrrJr rrencoder appendrh)roffsetsrkvlcategorys rWr%StataValueLabel._prepare_value_labelss "88Bbhh/88Bbhh/  ##B$&qEHh,,x= ,33DLLA*/1  t~~6H NN4== ) MMS]Q. .M MM"Q% HHOOH % FFaKFF$ ==5 F  88G288488F"((31tvv:%DFF 2T]]BrcURn[5nSnUR[R"US-UR 55 [ UR5SSRU5nUS;aSOSn[XVS-5nURU5 [S5H)nUR[R"S U55 M+ UR[R"US-UR55 UR[R"US-UR55 URH,nUR[R"US-U55 M. URH,n UR[R"US-U 55 M. URHn URX-5 M UR!5$) z Generate the binary representation of the value labels. Parameters ---------- byteorder : str Byte order of the output Returns ------- value_label : bytes Bytes containing the formatted value label iN )r utf8rBrc)r rwriterpackrr r r! _pad_bytesrangerrrrrgetvalue) r byteorderrbio null_byter lab_lenr)offsetrbtexts rWgenerate_value_label$StataValueLabel.generate_value_labelsq>>i  &++i#otxx89dll#CR(//9 (99"sWk2 'qA IIfkk#y1 2 &++i#otvv67 &++i#ot}}=>hhF IIfkk)c/6: ;XXE IIfkk)c/59 :HHD IId& '||~r) r r rrrrrrrNr)rr'rLiteral['latin-1', 'utf-8']rNonerr=)r3r rbytes) __name__ __module__ __qualname____firstlineno____doc__rrr9__static_attributes__rrWrrs7 IR % %*E %  %*CX2rrc6\rSrSrSrSSSjjrSrg)StataNonCatValueLabeliz Prepare formatted version of value labels Parameters ---------- labname : str Value label name value_labels: Dictionary Mapping of values to labels encoding : {"latin-1", "utf-8"} Encoding to use for value labels. cUS;a [S5eXlX0l[UR 5SS9UlUR 5 g)Nrr c US$)NrrFrs rWr0StataNonCatValueLabel.__init__..2s!r)key)rhr r sorteditemsrr)rr rrs rWrStataNonCatValueLabel.__init__&sL / /DE E !"    n  ""$r)r r rNr;)r r rdict[float, str]rr<rr=)r@rArBrCrDrrErFrrWrHrHs< "1: %%'%. %  %%rrHc\rSrSr%Sr0rS\S'SrS\S'\H,rS\\'\ "S S 5Hr S\ "S \ -5-\\ \-'M M. S r S \S'\ R"SS5SrS\S'\ "S 5Hwr \ R"S\ 5SrS\\'\ S:a\\==\ "S \ -5- ss'\ R"S\ R""S\55S\-r\ R""S\5r My SrS \S'\ R"SS5Sr\ "S 5Hwr \ R"S\5SrS\\'\ S:a\\==\ "S \ -5- ss'\ R"S\ R""S\55S\-r\ R""S\5rMy SSS\ R"S\ 5S\ R"S\5SS.rS\S'S(Sjr\S)S j5r\S*S!j5rS)S"jrS)S#jrS+S$jr\S,S%j5rS&rg')-ri7a  An observation's missing value. Parameters ---------- value : {int, float} The Stata missing value code Notes ----- More information: Integer missing values make the code '.', '.a', ..., '.z' to the ranges 101 ... 127 (for int8), 32741 ... 32767 (for int16) and 2147483621 ... 2147483647 (for int32). Missing values for floating point data types are more complex but the pattern is simple to discern from the following table. np.float32 missing values (float in Stata) 0000007f . 0008007f .a 0010007f .b ... 00c0007f .x 00c8007f .y 00d0007f .z np.float64 missing values (double in Stata) 000000000000e07f . 000000000001e07f .a 000000000002e07f .b ... 000000000018e07f .x 000000000019e07f .y 00000000001ae07f .z rPMISSING_VALUES)er bases.rB`r? float32_basez?B\Q {{43 >L%===&IJ1ML 2YmmD,/2!s q5 3 3rAv; . MM#v{{4'=>qALP {{3 2 ==|4Q7==|4Q7 "/     '   rrc\rSrSrSSjrSrg) StataParseric [[SS5Vs/sHo[R"SU354PM snS[R"[R54S[R"[R 54S[R"[R 54S[R"[R54S[R"[R54/-5Ul [R"[R5[R"[R5[R"[R5[R"[R 5[R"[R 5[R"[R5S .Ul [[[S55[S 5-5UlS S S SSSS .UlSnSnSnSnSSS[R"[ R""SU5S5[R"[ R""SU5S54[R"[ R""SU5S5[R"[ R""SU5S54S.UlSSSSSS.UlSSS[R"[ R""SS 5S5[R"[ R""SS!5S5S.UlS"S#S$S%S&S'S(.Ul1S)kUlgs snf)*NrBS)bhlfdQr\rlhr~srsr)rrH)rr)rrrrr)r~rrrr\)bilfrHrSrTrUrZri1i2i4f4f8u8)r~rrrr\r><_N_b_ndoifin_pi_rc_seendforraNULL_allbytecaseelseenumgotolongquadstrLwith_coef_cons_pred_skiprbreakcatchclassconstrlocalshortusingdeletedoubleexportfriendglobalinlinepragmabooleancomplexdefaulttypedefvirtualcontinuedelegateexplicitexternalfunctiontypename aggregate colvector eltypedef protected rowvectorstr#)dictr1rryrrrrr DTYPE_MAPr DTYPE_MAP_XMLlisttupleTYPE_MAP TYPE_MAP_XMLrr VALID_RANGEOLD_TYPE_MAPPINGrRNUMPY_TYPE_MAPRESERVED_WORDS)rr) float32_minr float64_minrs rWrStataParser.__init__s -21c] ;]AaS'" #] ;bhhrww'(bhhrxx()bhhrxx()bhhrzz*+bhhrzz*+    88BHH%88BJJ'88BJJ'88BHH%88BHH%88BGG$ 3 U5:.w?@  * ) 9 9  * 6=={;A>? 6=={;A>?  6=={;A>? 6=={;A>?   ! FMM$0CDQGH d$GHK    = [ )r@rArBrCrrErFrrWrrs[ rrc^\rSrSr%\rS\S'S1S2U4SjjjrS3SjrS3Sjr S4Sjr S5Sjr S3S jr S3S jr S6S jrS6S jrS6S jrS6SjrS6SjrS6SjrS6SjrS6SjrS7SjrS8SjrS3SjrS3SjrS9SjrS:SjrS:SjrS:SjrS:SjrS6SjrS;Sjr S;Sjr!S6Sjr"SS"jr%S3S#jr&S3S$jr'S?S%jr(S@SAS&jjr)\*"\+5SBSCS'jj5r,SDS(jr-SES)jr.SFS*jr/SGS+jr0\1S;S,j5r2\1S;S-j5r3SHS.jr4SIS/jr5S0r6U=r7$)J StataReaderi\z IO[bytes] _path_or_bufc >[T U]5 X lX0lX@lXPlX`lXplXlXl Xl Xl SUl Xl SUlSUlURcSUl O&[!U ["5(aU S::a [%S5eSUlSUlSUlSUlSUlSUlSUlSUl[7[8R:5Ulg)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_enteredrrarh _close_file_missing_values_can_read_value_labels_column_selector_set_value_labels_read _data_read_dtype _lines_read_set_endiannesssysr3_native_byteorder) r path_or_buf convert_datesconvert_categoricals index_colconvert_missingpreserve_dtypescolumnsorder_categoricals chunksize compressionr7 __class__s rWrStataReader.__init__as ,%9"# / / #5 %0"' /#$ ?? "DOIs++yA~MN N7;$&+#$)!"''+ !0!?rcH[US5(dUR5 gg)z; Ensure the file has been opened and its header data read. rN)hasattr _open_fileres rW _ensure_openStataReader._ensure_opens t^,, OO -rcxUR(d"[R"S[[ 5S9 [ UR SURSURS9n[URS5(aBURR5(a#URUl URUlONU [URR!55Ul SSS5 URRUlUR#5 UR%5 g!,(df  NJ=f)zN 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.rvrbF)r7is_textrseekableN)rrrResourceWarningrr)rrrrhandlerrcloserrread _read_header _setup_dtype)rhandless rWrStataReader._open_files}} MMW+-     & &  11))   7>>: . .7>>3J3J3L3L 'D &}}D $+GNN,?,?,A$B!#0066D    s >)D++ D9cSUlU$)zenter context managerT)rres rW __enter__StataReader.__enter__s  rcHUR(aUR5 ggrk)r)rexc_type exc_value tracebacks rW__exit__StataReader.__exit__s        rc[R"S[[5S9 UR(aUR 5 gg)zClose the handle if its open. .. deprecated: 2.0.0 The close method is not part of the public API. The only supported way to use StataReader is to use it as a context manager. zThe StataReader.close() method is not part of the public API and will be removed in a future version without notice. Using StataReader as a context manager is the only supported method.rvN)rr FutureWarningrrres rWrStataReader.closes=   S ')          rcBURS:aSUlgSUlg)z3 Set string encoding which depends on file version vrr N)_format_versionr res rW _set_encodingStataReader._set_encodings    # %&DN$DNrch[R"SURRS55S$)Nr~rBrrrrrres rW _read_int8StataReader._read_int8)}}S$"3"3"8"8";<r0r~ r rrB)+rrrar1rh_version_errorrJr2r@rArF_nvar _get_nobs_nobs_get_data_label _data_label_get_time_stamp _time_stamprR_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_varlistrY_srtlist _get_fmtlist_fmtlist _get_lbllist_lbllist_get_variable_labels_variable_labelsres rWr]StataReader._read_new_header se r""4#4#4#9#9!#<=    6^224;O;O2PQ Q  r"!%!2!2!7!7!:f!D## r"#'#7#73#>D   DDUDUDW  q!^^%  r"//1 r"//1 r" q! q!"..025"..025"..025!--/!3'+'7'7'9B'>$&*%C%C%E" q!"..014++-1"&"2"2"4r"9(,(8(89L9L(M% t~ t223))+  t223..tzzA~>sC  t112))+  t;;<))+  t99: $ 9 9 ;rcURRU5 /n/n[UR5HnUR 5nUS::a-UR U5 UR [ U55 MFUR URU5 UR URU5 M X#4$![an[SUS35UeSnAff=f)Ncannot convert stata types []) rrr1rtrAr"r rrKeyErrorrh)r seek_vartypestyplistdtyplist_typerrs rWrStataReader._get_dtypesAs }-tzz"A##%Cd{s#C)UNN4#4#4S#9:OOD$6$6s$;<#   U$'CC5%JKQTTUs<? ?  ! !S (__&F<< 1 1 6 6v >? ?  ! !C '<< 1 1 6 6r :; ;<< 1 1 6 6r :; ;rcURS:a:UR5nURRU5R S5$URS:Xa:UR5nUR URRU55$URS:a*UR URRS55$[ 5e)Nr0r rcr)r1r6rrdecoderrhrs rWryStataReader._get_time_stamps   3 &__&F$$))&188A A  ! !S (__&F<< 1 1 6 6v >? ?  ! !C '<< 1 1 6 6r :; ;, rcURS:Xa=URRS5 URSUR--S-S-$URS:aUR 5S-$[ 5e)Nrcrrr0)r1rrrrtrRrhres rWr%StataReader._get_seek_variable_labelsss   3 &    " "1 %//2 ?CbH2M M  ! !S (##%* *, rc 2 [US5UlURS;a&[[R URS95eUR 5 UR 5S:XaSOSUlUR 5UlURRS5 UR5Ul UR5UlUR5UlUR#5UlURS:a?URRUR5Vs/sHn[U5PM nnOURRUR5n[&R("U[&R*S9n/nUHFnX`R,;a UR/UR,U5 M2UR/US - 5 MH UVs/sHopR0UPM snUlUVs/sHopR8UPM snUlURS:aS[=UR5V s/sH,oR?URRS55PM. sn Ul OR[=UR5V s/sH,oR?URRS55PM. sn Ul URCURS-5SSUl"URG5Ul$URK5Ul&URO5Ul(URS:afUR 5n URS:aURS5nOURU5nU S:XaOURRU5 MeURRW5Ul,gs snfs snf![aFnS R5UV s/sHn [7U 5PM Os sn fsn 5n [S U S 35UeSnAff=fs snf![aFnS R5UV s/sHn [7U 5PM Os sn fsn 5n [S U S 35UeSnAff=fs sn fs sn f)Nr)rrrorrsrerBrhrirrx,rrzcannot convert stata dtypes [rrprrr)-rar1rhrsrJr2r6r@ _filetyperrrArtrurvrwrxryrzr frombufferrrr"rrjoinr rrr1rrrYrrrrrrrrOrLtellr)rr_r-rbuftyplistbtprrr invalid_typesinvalid_dtypesr data_typedata_lens rWr^StataReader._read_old_headers":a=1   'J J^224;O;O2PQ Q !%!2c!9#s* q!&&( ^^% //1//1   # %'+'8'8'='=djj'IJ'I!s1v'IGJG##((4C}}S9HG...NN4#8#8#<=NN28,   W;BC7C]]3/7CDM Y=DEWcnnS1WEDN   # %BG BSBSQ T..33B78BSDM BGtzzARARA T..33A67ARDM..tzzA~>sC ))+ ))+ $ 9 9 ;   # % OO- ''#-#//1H#//1H>!!&&x0#//446oKD WHHg%>gc!fg%>?M;M?!LMSV V WF Y XXw&?w!s1vw&?@N<^ URS:aURRS 5 GM4SUlg)NrTrcs,,A%;&&w/7 ##s*!!&&q)CD#'rcURRUR5 SS0UlURR S5S:wagUR S:XaUR 5nOvURR S5nUR S:XaSOSnURS :XaUS UUS SU- -nOUS UUS U-S-n[R"S U5S nUR5nUR5nURR U5nUS :XaUS SRUR5nO [U5nXpR[U5'GM<)N0rrsGSOrcrr0rrirrrrr)rrrGSOrr1rIr@rrr;rFrr r )rv_orv_sizerlengthva decoded_vas rW _read_strlsStataReader._read_strlsSsV t//09  %%a(F2##s*'')'',,R0"22c9q??c)a-#a2;*@@Ca-#q6zn*==CmmC-a0""$C&&(F""''/Bcz"X__T^^< !W !+HHSX 3rcBSUlURURS9$)NTnrows)rrrres rW__next__StataReader.__next__rs#yyty//rc>Uc URnURUS9$)z Reads lines from Stata file and returns as dataframe Parameters ---------- size : int, defaults to None Number of lines to read. If None, reads whole file. Returns ------- DataFrame r)rr)rsizes rW get_chunkStataReader.get_chunkvs# <??Dyyty$$rc ^UR5 Uc URnUc URnUc URnUc URnUc UR nUc UR nUc URnUc URnURS:XaUS:XaSUl SUl [URS9n [U R5H\upURU n [!U ["R$5(dM5U R&S:wdMGXR)U 5X'M^ UbUR+X5n U $UR,S:a(UR.(dSUl UR15 UR2ceUR2n URUR4- U R6-nXR6-n[9X5nUS::aU(aUR;5 [<eUR4U R6-nUR>RAURBU-5 [9XRUR4- 5n["RD"UR>RGU5U US9nU=R4U- slUR4UR:XaSUl SUl URHURJ:wa7URM5ROUR$RQ55nU(aUR;5 [SU5S:Xa[URS9n O0[RT"U5n [WUR5U lUc([YUR4U- UR45U l-UbUR+X5n []XR^5H<un n[!U[`5(dMXRcURd5X'M> URgU 5n [UR5V Vs/sH un nUcM U PM nn n["R$"[h5nUHinU RjSS2U4R$n U UURU4;dM7U RmUU RjSS2U4R)U 55 Mk URoX5n U(al[URp5HSun m[sU4Sj[t55(dM&U RmU [wU RjSS2U 4T55 MU U(a7UR,S:a'URyXRzUR|U5n U(Gdo/nS nU GH>n XR$n U ["R$"["R~5["R$"["R54;a'["R$"["R5n SnOU ["R$"["R5["R$"["R5["R$"["R54;a&["R$"["R5n SnURXU R)U 545 GMA U(a[R"[U55n Ub U RU RU55n U $s snn f) NrT)r rrcrc3F># UHnTRU5v M g7frk)r).0date_fmtrs rW #StataReader.read..sN Hs~~h// s!rF)Krrrrrrrrrvrrr$rrr rrrrycharr_do_select_columnsr1rrrrrrNr StopIterationrrrrrr@rbyteswapr newbyteorderr from_recordsr%r&rKrPrrarr _insert_strlsrilocisetitem_do_convert_missingrr _date_formatsr_do_convert_categoricalsrrfloat16rrrrrrr" from_dictr set_indexpop)rrrrr r r r r rr)rdtry max_read_lenread_lenr7 read_linesraw_datardtyp valid_dtypes object_typeidx retyped_dataconvertrs @rWrStataReader.reads    //M  '#'#=#=  ""33O  ""33O ?mmG  %!%!9!9   I =JJE JJ!O!*.D '"DOT]]3D#DLL1^^A&b"((++ww#~$(I$4$4R$8 2 "..t=K  C '$2I2I*.D '    {{&&&  T%5%55G >>)x. q=$'') !!ENN2 t22V;< T-=-= => ==    " "8 ,E  J&   tzz )*.D '"DO ??d44 4((*//0K0K0MNH   # # % x=A T]]3D))(3D /DL  #  :-t/?/?DJ  **49DD--0HC#s## IOODLL9 1!!$'*34>>)BW)Bgad)B Whhv& CIIaf%++E[$..*=>> c499QV#4#;#;E#BC ''> #DMM23N NNNMM>tyyAPST3 D$8$83$>00,,dmm=ODLG RXXbjj1288BJJ3GHHHHRZZ0E"GHHRWW%HHRXX&HHRXX& HHRXX.E"G##Ss)*:*:5*A$BC **4 +=>  >>$((9"56D WXs  ]]c0n[[UR55GHnURUnXPR;aM$[ [ U5nURUupgURSS2U4nURn X:X:-n U R5(dMU(a[R"[R"U 55Sn [R"XSS9up[U[S9n[!U 5H'unn[#U5nXU:HnUURU'M) OUR$nU[R&[R(4;a[R(n[UUS9nURR*S(dUR-5n[R.URU 'XU'GM U(a,UR15HunnUR3UU5 M U$)NrT)return_inverserx WRITEABLE)r1rr rrr r rrrrnonzeroasarrayuniquer'rrrryrrflagsrnanrNr )rrr  replacementsr)rnminnmaxseriessvalsmissing missing_locumissing umissing_loc replacementjumrrryrrbs rWr StataReader._do_convert_missings s4<<()A--"C***sC.C))#.JDYYq!t_FNNE| 5G;;== jjG)<=a@ )+6?SW)X&$V6: &x0EAr$5b$9M%a&78C,9K$$S) 1  RZZ 88JJE$V59 "**00=#."2"2"4K02vv ##G,)OK*L *002 U c5)3 rc D[US5(a[UR5S:XaU$[UR5HUup#US:waM UR X!R SS2U4Vs/sHo@R[U5PM sn5 MW U$s snf)Nrrr)rrrrrr rr )rrr)rks rWrStataReader._insert_strlsMstU##s488}'9K .FAcz MM! !Q$H1hhs1v.H I /  Is/!B cUR(Gd;[U5n[U5[U5:wa [S5eUR UR 5nU(a(SR [U55n[SU35e/n/n/n/n UHn UR RU 5n URURU 5 URURU 5 URURU 5 U RURU 5 M X`l Xpl Xl Xl SUlX$)Nz"columns contains duplicate entriesz, z&--bl;&--h7 %8"&biik!2J3 (99*EH&$HJJUK "))3 *;<"))3S *:;{-|01> /"3 7DDFB$("q&)9$:M- -0HHG   C%S/s2!3s3F H'AHHc:UR5 UR$)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. )rrxres rW data_labelStataReader.data_labels$ rc:UR5 UR$)z" Return time stamp of Stata file. )rrzres rW time_stampStataReader.time_stamps rctUR5 [[URUR55$)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 )rrrPrrres rWvariable_labelsStataReader.variable_labelss,0 C t'<'<=>>rc\UR(dUR5 UR$)a 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 )rrrres rWrStataReader.value_labelss%0&&  # # %%%%r)1rr@rrrrrrrrrrxrrrrr rrrr1rrrrrrvrtrrrrr~r}rrrrr|r{rrrzrrrrrr) TTNFTNTNinferN)rFilePath | ReadBuffer[bytes]rrrrr  str | Noner rr rr Sequence[str] | Noner rr int | Nonerr.r7StorageOptions | Nonerr=r>)rr1)r'ztype[BaseException] | Noner(zBaseException | Noner)zTracebackType | Nonerr=)rra)rr?)rXrarztuple[int, ...])rrarz,tuple[list[int | str], list[str | np.dtype]])rz list[str]r{)r_r?rr=)rr|)rr?rr )rr$rk)rrarr$)NNNNNNNN)rrar bool | Nonerrcr r_r rcr rcr r`r rcrr$)rr$r rrr$rr$rr$)rr$r  Sequence[str]rr$) rr$rFdict[str, dict[float, str]]r=rer rrr$)rzdict[str, str])rrf)8r@rArBrC_stata_reader_docrDr}rrrr$r*rr2r6r;rArFrIrLrOrRrUrYrr]rrrrrrurwryrr^r rrrrrr_read_method_docrr rrr rrSrVrYrrE __classcell__rs@rWrr\sG #%) $ % $(,#' $*115/@1/@/@# /@  /@  /@/@&/@!/@/@(/@//@ /@/@b> ,((   $%@@RRRRRR@ .50%"!%),0 $'+'+(,*.UU#U* U  U % U%U&U(U U Un,\@LL6L L ! L  L\  (  ?6&&rrTFr]) rrr r r r r riteratorrr7c [UUUUUUUUUU U S9 n U (dU(aU $U  U R5sSSS5 $!,(df  g=f)N) rrr r r r r rr7r)rr) r6rrr r r r r rrkrr7readers rW read_statarnsQ #1''-' F9 {{} s A ActUR5S;agUR5S;ag[SUS35e)N)rilittleri)rhbigrhz Endianness r)lowerrh) endiannesss rWrr@s>_,    | +;zl/BCCrc|[U[5(aUSU[U5- --$USU[U5- --$)zI Take a char string and pads it with null bytes until it's length chars. r()rr?rrrs rWr0r0IsC$g#d)!3444 &FSY./ //rctUS;a$[R"[R5$[SUS35e)zC Convert from one of the stata date formats to a type in TYPE_MAP. )rsr8rzr:r|r<rr=rr>rr?rr@rz not implemented)rryrNotImplementedError)rs rW_convert_datetime_to_stata_typeryRs;  xx ##!GC50@"ABBrc0nUHnXRS5(d SX-X'X1;a&URURU5X05 MO[U[5(d [ S5eURX0U05 M U$)N%z0convert_dates key must be a column or an integer)rupdaterKrrarh)rvarlistnew_dictrLs rW_maybe_convert_to_int_keysrksH!,,S11!$}'9!9M  > OOW]]3/1CD Ec3'' !STT OOS"45 6 OrcUR[RLa*[[ UR 55n[ US5$UR[RLagUR[RLagUR[RLagUR[RLagUR[RLag[SUS35e) 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. rprobject_rrrrMrrrrrrx)ryrIrs rW_dtype_to_stata_typerys" zzRZZ( fnn(EF8Q rzz ! rzz ! rxx  rxx  rww !Jug_"EFFrc"US:aSnO SnU(agUR[RLam[[ UR 55nXT:a/US:ag[ [RUR55eS[[US55-S-$U[R:XagU[R:Xag U[R:Xag U[R[R 4;ag [#S US 35e)ar 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" rcrz%9sr{rBrz%10.0gz%9.0gz%12.0gz%8.0grr)rprrrrrrhrrJrr rMrrrrrrx)ryrI dta_version force_strl max_str_lenrs rW_dtype_to_default_stata_fmtrs&S   zzRZZ' fnn(EF  !c! !>!E!Efkk!RSSSXq)**S00 "**  "**  "((  277BHH% %!Jug_"EFFrcompression_optionsfname)r7rc^\rSrSr%SrSrSrS\S'S*SS.S+U4S jjjjrS,S jr S-S jr S.S jr S/S jr S/Sjr S0SjrS1SjrS/SjrS2SjrS3SjrS0SjrS0SjrS0SjrS0SjrS0SjrS0SjrS0SjrS0SjrS0SjrS4S5SjjrS0SjrS0SjrS0S jrS0S!jr S0S"jr!S0S#jr"S/S$jr#S6S%jr$S7S&jr%\&S8S'j5r'S9S(jr(S)r)U=r*$): StataWriteriaj 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() rrr<r Nrc >[T U]5 X lUc0OUUlX@lX`lXplXlXl/Ul [R"/[S9Ul XlSUl0UlUR#U5 XlUc[&R(n[+U5UlXl[R0[R2[R4S.Ulg)Nrx)rrr)rrrr _write_indexrzrxr_non_cat_value_labels _value_labelsrrr_has_value_labelsr _output_file_converted_names_prepare_pandasr7rr3rr@_fnamerrrtype_converters) rrrr write_indexr3rVrSrYrr7rrs rWrStataWriter.__init__ s  $1$9b}'%% /%1"46!#"D!9'.257 T".   I))4 %'XXBHH277KrcURRRURUR55 g)zC Helper to call encode before writing to file for Python 3 compat. N)r!rr.r!r )rto_writes rW_writeStataWriter._writeF s) !!(//$.."ABrcNURRRU5 g)z/ Helper to assert file is open before writing. N)r!rr.rbs rW _write_bytesStataWriter._write_bytesL s !!%(rc/nURcU$URR5Hup4X0R;aURUnO*X1R;a [ U5nO[ SUS35e[ XR5(d[SUS35e[XTUR5nURU5 M U$)zK Check for value labels provided for non-categorical columns. Value labels zCan't create value labels for z!, it wasn't found in the dataset.z6, value labels can only be applied to numeric columns.) rrNrr r rrryrhrHr r")rrnon_cat_value_labelsr labelscolnamesvls rW_prepare_non_cat_value_labels)StataWriter._prepare_non_cat_value_labelsR s=?  % % -' '#99??AOG/////8LL(g,4WI>,, $DM$7$788!4WI>>>(HC ' ' ,' B($#rcURVs/sHn[U[5PM nn[U5(dU$U=R[ R "U5-sl[Rn/n[X5GHupgU(Ga[XURS9nURRU5 XRRR nU[ R":Xa [%S5eXRRR&R)5n U R+5U"U5:aU[ R,:Xa%[ R "[ R.5nO]U[ R.:Xa%[ R "[ R05nO$[ R "[ R25n[ R "XS9n U"U5XS:H'URXi45 GMURXaU45 GM [4R6"[9U55$s snf)zr Check for categorical columns, retain categorical information for Stata file and convert categorical data to int )rzCIt is not possible to export int64-based categorical data to Stata.rxrr)rrrrrrrrryrPrr rr"r codesryrrhrrrMrrrrr$rr) rrryis_catrydata_formattedr col_is_catrrks rW_prepare_categoricals!StataWriter._prepare_categoricalss s DH;;O;%*U$45;O6{{K "((6"22!2!I!I"40OC%di$..I""))#. ++11BHH$$A,,4499;::<#9%#@@' " 2"((* " 2 " 4XXf:F(>e'D|$%%sm4%%sI&675 16""4#788GPsIcUHnXRnU[R[R4;dM7U[R:XaURSnOURSnXR U5X'M U$)zn Checks floating point data columns for nans, and replaces these with the generic Stata for missing value (.) rr\)ryrrrrRr)rrr-ryr.s rW _replace_nansStataWriter._replace_nans ss AGMMERZZ00BJJ&"&"5"5c":K"&"5"5c":K'..5 rcg)zNo-op, forward compatibilityNrFres rW_update_strl_namesStataWriter._update_strl_names rcUHGnUS:dUS:dMUS:dUS:dMUS:dUS:dM-US:wdM5URUS5nMI U$)a Validate variable names for Stata export. Parameters ---------- name : str Variable name Returns ------- str The validated name with invalid characters replaced with underscores. Notes ----- Stata 114 and 117 support ascii characters in a-z, A-Z, 0-9 and _. AZazr9r)replacerrr-s rW_validate_variable_name#StataWriter._validate_variable_name sS(ASAGWCWCH||As+ rc0n[UR5nUSSnSn[U5HupgUn[U[5(d [ U5nUR U5nXpR ;aSU-nSUSs=::aS::aO OSU-nUS[[U5S5nXx:Xd^URU5S:aES[ U5-U-nUS[[U5S5nUS- nURU5S:aMEXrU'XsU'M [U5UlUR(aD[X45H5upX:wdM URU URU 'URU M7 U(ay/n UR5HupUSU3n U RU 5 M [R!S R#U 55n [$R&"U [([+5S 9 X lUR/5 U$) a| Checks column names to ensure that they are valid Stata column names. This includes checks for: * Non-string names * Stata keywords * Variables that start with numbers * Variables with names that are too long When an illegal variable name is detected, it is converted, and if dates are exported, the variable name is propagated to the date conversion dictionary Nrrrrr*rBz -> z rv)rr rrr rrrNrrXr%rrPrNr"rrJrrrrrrr)rrconverted_namesr original_columnsduplicate_var_idr/r orig_namer-oconversion_warningrrs rW_check_column_namesStataWriter._check_column_names s02t||$"1: )GAIdC((4y//5D***Tzd1g$$Tz,#c$i,-D$mmD)A-%5!66=D 4#c$i"45D$)$ mmD)A- .2 *AJ5*8W~    G66-1-@-@-CD''*++A.7 !# #2#8#8#: " 8D62"))#.$;"((7I)JKB MM!+-  !0 ! rc/Ul/UlUR5Hgup#URR[ X0R U55 URR[ X0R U55 Mi grk)r<rrNr"rrr)rrrrys rW_set_formats_and_types"StataWriter._set_formats_and_types sb"$ "$  ,,.JC LL   ;E99S> R S LL   4UIIcN K L)rcdUR5nUR(a'UR5n[U[5(aUnUR U5n[ U5nURU5n[R"SURS5Ul URU5nUVs/sHoDRPM nnURRU5nU=RU-sl UR R#U5 UR%U5nURuUlUlXlURR-5UlUR0nUHMnXR2;aM[4R6"XR8S5(dM>SUR2U'MO [;UR2UR.5UlUR2H>n [=UR2U 5n [R8"U 5UR>U 'M@ URA5 URCU5 UR2bGUR2H6n [U [D5(dMUR2U URFU 'M8 ggs snf)NFrBrrs)$rr reset_indexrr$rrrrrepeatrrrr r rBrextendrnobsnvarrtolistr}rrrrryrryr_encode_stringsrrar<) rrtemprrnon_cat_columnshas_non_cat_val_labelsrrrLnew_types rWrStataWriter._prepare_pandas s<yy{   ##%D$ **''-$D)!!$'"$5$**Q-!@ $AA$G2FG2F3;;2FG!%!2!2?!C "88 !!"67))$/#zz 49 ||**, C)))ty44+/##C(  9    &&C6t7J7J37OPH!xx1FKK '  ##F+    ***c3''(,(;(;C(@DLL%+ +EHs4J-cNURn[US/5n[UR5Hup4X1;dXB;aMURUnURnUR [ RLdMK[USS9nUS:Xd*[U5S:XdURn[SUS35eURURRUR5n[[!UR"55UR$::dMXRU'M g) 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_strlTrrfrzColumn `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)rrOrrryrprrrrrrhr r!r rrr_max_string_length) rr convert_strlr)rrIryinferred_dtypeencodeds rWrStataWriter._encode_stringsa s++ t_b9  *FA!S%8YYs^FLLEzzRZZ'!,VD!A'83F q8H ++C$ ))C.,,33DNNC)w)GH../&-IIcN1+rc [URSURSURS9UlURR SbnURR [5sUlURlURRRURR 5 URURURS9 UR5 UR5 UR!5 UR#5 UR%5 UR'5 UR)5 UR+5 UR-5 UR/5nUR1U5 UR35 UR55 UR75 UR5 UR95 SSS5 g![:anURR=5 [?UR[@[BRD45(a[BRFRIUR5(ad[BRJ"UR5 Ue![La4 [NRP"SURS3[R[U5S 9 Uef=fUeSnAff=f!,(df  g=f) aI 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)rSrVz!This save was not successful but z. could not be deleted. This file is not valid.rv)+r)rrr7r!rrrrcreated_handlesr" _write_headerrxrz _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 Exceptionrrr osPathLikepathisfileunlinkOSErrorrrrr)rrecordsexcs rW write_fileStataWriter.write_file sN8 KK )) 00  \||''1=:>9L9Lgi6!4<<#6 ,,33DLL4G4GH" ""#//D>277>>KKDD $++. # ? }MBB+'7'9     C  sPBK;D%G** K4A7K, J K:K K K  KKK K'c>URb[URR[5(deURRURsoRlURRR UR 55 gg)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)rrr!rrr.r2)rr4s rWrStataWriter._close sq    (dll117;; ;;'+||':':D# UHn[U5S:v M g7f)N)ord)rr-s rWr5StataWriter._write_variable_labels..[ s 4<<?!DI* ""4(??ocmm.LLoFA*C---,,.++ 9!. ))"-B /HHZsfH= C5 #s  I,,U3  '!..t?E#s %&(U&AA#/.s .F F cBURUR55 grk)rtobytesrrs rWrStataWriter._write_data s '//+,rcUS- nU$)NrurF)rs rWr0StataWriter._null_terminate_str s V rcVURU5RUR5$rk)r0r!r )rrs rWr&!StataWriter._null_terminate_bytes s"''*11$..AAr)r@rrrrxrrrrrzrrrrr<r!rrr7rrr})NTNNNNr]N)rFilePath | WriteBuffer[bytes]rr$rdict[Hashable, str] | Nonerrr3r_rVdatetime | NonerSr_rYrYrr.r7rbr'dict[Hashable, dict[float, str]] | Nonerr=)rr rr=)rbr?rr=)rr$rzlist[StataNonCatValueLabel]rdr>rr rr rr'rr=)rr$rr=NNrSr_rVrZrr=)rnp.rec.recarray)rr`rr=)rr rr )rr rr?)+r@rArBrCrDrr r}rrrrrrrrrrrrrrrrrrrrrrrrrrrrCrr staticmethodr0r&rErirjs@rWrrs L\-6I*6 59 $&*!%6:*115$LAE$L,$L$L2 $L  $L  $L$$L$L4$L($L/$L>$L $L$LLC ) $$ $$B(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. Nc*US;a [S5eX0lXlX lSS0UlUc[ R n[U5UlSnSnSUl US:Xa S nSnS Ul O US :XaS nOS nSSSU- --Ul X`l XPl g)Nrbz,Only dta versions 117, 118 and 119 supportedrrrrErr rcrrr0rrrr) rh_dta_verdfr  _gso_tablerr3rr@r _o_offet _gso_o_type _gso_v_type)rrkr rfr3 gso_v_type gso_o_typeo_sizes rWrStataStrLWriter.__init__ s / )KL L  v,   I))4    c>FJ&DN ^FFa1v:./ %%rc,Uup#X RU--$rk)rm)rrLrrs rW _convert_keyStataStrLWriter._convert_key s==1$$$rcURnURn[UR5nX RnURVs/sHoUUR U54PM nn[ R "UR[ RS9n[UR55Hbunup[U5HKun up\Xn U cSOU n URU S5nUcU S-US-4nXU 'URU5XxU 4'MM Md [UR5HupUSS2U4X%'M X4$s snf)aP 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 rxNrrB) rlrkrr rKremptyrrriterrowsgetru)r gso_tablegso_dfr selectedr col_indexrArrrowr/rrrLr)s rWgenerate_tableStataStrLWriter.generate_table s+:OO v~~&,,':>,,G,37==-., Gxxbii8&x'8'8':;MAz(3 8ChKbSmmC.;q5!a%.C%(cN!..s3T  4<  -FAq!t*FK.  !Hs Ec B[5n[SS5n[R"URS-S5n[R"URS-S5nURUR -nURUR -nURS-nUR5HupU S:XaM U upURU5 UR[R"Xk55 UR[R"X|55 URU5 [U S5n UR[R"U[U 5S -55 URU 5 URU5 M UR5$) aw 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:rrrErir rB) rr?rr/r@rornrNr.rr2)rr{r4gsogso_typenullv_typeo_typelen_typestrlvorr utf8_strings rW generate_blobStataStrLWriter.generate_blobD sB:iE7#;;t4c:{{4??S0!44#3#334#3#33??S(!)HDV|DA IIcN IIfkk&, - IIfkk&, - IIh  g.K IIfkk(C ,", "<", "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() rrcNrc >/UlU bURRU 5 [T U] UUUUUUUUU U U S9 0UlSUlg)N)r3rVrSrYrrr7r)rrrr_map _strl_blob)rrrrrr3rVrSrYrrr7rrs rWrStataWriter117.__init__ sj".0  #    % %l 3     !!+%#+  %' rc[U[5(a [US5n[SU-S-S5U-[SU-S-S5-$)zSurround val with r rirhzr releaserhMSFLSFr3r0r>rEKrcrNNrrr:rHrrrBr$r% timestampheader)r@rr?rr.rr  _dta_versionrr/rrr!r rrr'rrhrr(rRr2)rrSrVr3r4 nvar_type nobs_sizerH encoded_label label_size label_lenr)r)rRr*r+stata_tss rWrStataWriter117._write_header sA OO  % w78i $))E#d&7&7"8'BINO $))I,6?%MN,,3C  $))FKK (=tyyI3OP,,3C  $))FKK (=tyyI3OP#-#9 3Br T^^4  --4S# KK 6M8JK !1  $))M734  !JJ11AB B  6?v5FG5FAu 5F G    &++, -!!+. / U2w// $))Hk23 $))CLLNH=>HsKcUR(d8SURRR5SSSSSSSSSSSSS.UlURRR URS5 [ 5nURR 5H6nUR[R"URS-U55 M8 URURUR5S55 g)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_namesrYcharacteristicsrstrlsrstata_data_close end-of-filerrN)rr!rrrrrkr.rr/r@rrr2)rr4rs rWrStataWriter117._write_mapH s yy||**//1"#%&#$#$ !$% DI"   5!12i99##%C IIfkk$//C"7= >& $))CLLNE:;rc$URS5 [5nURH6nUR[R "UR S-U55 M8 URURUR5S55 g)Nrr>) rrrr.rr/r@rrr2)rr4rs rWr$StataWriter117._write_variable_typesf sf )*i<  $))CLLN4DEFrcURS5 [5nURS:XaSOSnURHPnUR U5n[ USSR UR5US-5nURU5 MR URURUR5S55 g)Nrrcr*r,rB) rrrr}r0rer!r r.rrr2)rr4vn_lenrs rWrStataWriter117._write_varnamesm s $i((C/SLLD++D1D!$s)"2"24>>"BFQJOD IIdO! $))CLLNJ?@rcURS5 URS:aSOSnURURSU-URS--S55 g)Nrrdrrr(rB)rrrrr)r sort_sizes rWrStataWriter117._write_sortlistx sO $**S0Aa  $))Gi$7499q=$I:VWrcNURS5 [5nURS:XaSOSnURH7nUR [ UR UR5U55 M9 URURUR5S55 g)Nrrcrr) rrrr<r.rer!r rrr2)rr4fmt_lenrs rWrStataWriter117._write_formats} sx #i))S0"b<?rcURS5 [5nURS:XaSOSn[UR5HunSnUR U(aUR UnURU5n[USSRUR5US-5nURU5 Mw URURUR5S55 g)Nrrcr*r,rrB)rrrr1rrr}r0rer!r r.rrr2)rr4vl_lenr)r encoded_names rWr'StataWriter117._write_value_label_names s ,-i((C/Styy!AD%%a(||A++D1D)$s)*:*:4>>*JFUVJWL IIl #" $))CLLN4GHIrc6URS5 [5nURS:XaSOSn[SUS-5nURc][ UR 5HnURU5 M URURUR5S55 gURHnXPR;adURUn[U5S:a [S5eURUR5nUR[XrS-55 MvURU5 M URURUR5S55 g![ an[SUR35UeSnAff=f) NrYrcri@rrBr:zDVariable labels must contain only characters that can be encoded in )rrrrerr1rr.rrr2rrrhr!r UnicodeEncodeError) rr4rr?rrrHrrs rWr%StataWriter117._write_variable_labels s_ *+i((C/Sr6A:.  (499% % &   dii 8IJ K 99C+++--c2u:?$%UVV#ll4>>:G .1*=> %  $))CLLN4EFG*$--1^^,<>s1E00 F:FFchURS5 URURSS55 g)Nrr)rrrres rWr%StataWriter117._write_characteristics s+ *+ $))C):;s)rrrQrRs rWrStataWriter117._write_data sA   )$ '//+, *%rc|URS5 URURURS55 g)Nr)rrrrres rWrStataWriter117._write_strls s- ! $))DOOW=>rcg)zNo-op in dta 117+NrFres rWr&StataWriter117._write_expansion_fields rrc:URS5 [5nURHAnURUR5nUR US5nUR U5 MC URUR UR5S55 g)Nrlbl) rrrr9r@rr.rr2)rr4r$labs rWr"StataWriter117._write_value_labels sw (i$$B))$//:C))C'C IIcN% $))CLLNNCDrc~URS5 UR[SS55 URS5 g)Nrz r r)rrr?res rWr$StataWriter117._write_file_close_tag s4 +, %89 'rcURR5H?upXR;dMURRU5nX RU'MA g)zn Update column names for conversion to strl if they might have been changed to comply with Stata naming rules N)rrNrrK)rorignewrs rWr!StataWriter117._update_strl_names sO ..446ID)))((..t4*-""3'7rc"[U5VVs/sH+up#URUS:XdX0R;dM)UPM- nnnU(a>[XURS9nUR 5upgUnUR U5UlU$s snnf)zO Convert columns to StrLs if either very large or in the convert_strl variable rre)rrrrgrrrr)rrr)r convert_colssswtabnew_datas rWrCStataWriter117._convert_strls s$D/ )||A%'32D2D+D )  !$d>O>OPC..0MCD!//4DO  s (B B cN/Ul/UlUR5Hup#X R;n[ UUR UUR US9nURRU5 URR[X0R UU55 M g)N)rr) rr<rNrrrrr"rc)rrrryrrs rWr%StataWriter117._set_formats_and_types s   ,,.JC 2 22J- # --% C LL   $ LL  ( # K )r)rrrr<r) NTNNNNNr]N)rrXrr$rrYrrr3r_rVrZrSr_rYrYrSequence[Hashable] | Nonerr.r7rbrr[rr=)r str | bytesrr rr?)rr rr=r^r_r>rdr])r@rArBrCrDrrrrarrrrrrrrrrrrrrrrrrCrrErirjs@rWrr smSjL 59 $&*!%6:26*115#AE#,##2 #  #  #$##4#0#(#/#># ##JXX 4"&&*8?8?$8?  8?t<<G AX @ JH@=& ? E( .$rrc^\rSrSr%SrSrS\S'S SS.S U4SjjjjrS S jrS r U=r $)StataWriterUTF8iu 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() r zLiteral['utf-8']r Nrc >U cURSS::aSOSn O5U S;a [S5eU S:XaURSS:a [S5e[TU] UUUUUUUUU U U U S9 Xlg) NrBir0rd)r0rdz"version must be either 118 or 119.zKYou must use version 119 for data sets containing more than32,767 variables) rrr3rVrSrYrrrr7)rrhrrr)rrrrrr3rVrSrYrrfrr7rrs rWrStataWriterUTF8.__init__ds" ?!ZZ]e3cG J &AB B ^ 1  5#    '#!!+%%#+  $rcUHnn[U5S:a*US:dUS:aUS:dUS:aUS:dUS:aUS:wd S[U5s=::aS :d O US ;dM\URUS5nMp U$) 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. The only limitation is in the ascii range where the characters supported are a-z, A-Z, 0-9 and _. r,rrrrrrr>×÷)r=rrs rWr'StataWriterUTF8._validate_variable_namesy*AFSLSAGSAGSAGS#a&&3& $||As+ r)r) NTNNNNNNr]N)rrXrr$rrYrrr3r_rVrZrSr_rYrYrrrfrarr.r7rbrr[rr=r\) r@rArBrCrDr r}rrrErirjs@rWrrs^@#*I) 59 $&*!%6:26"*115*$AE*$,*$*$2 *$  *$  *$$*$*$4*$0*$*$(*$/*$>*$ !*$*$X##rr)rr'rr rr'rd)r6r^rrrrr r_r rr rr r`r rrrarkrrr.r7rbrzDataFrame | StataReader)rsr rr )rr rrarr )rr rr|)rrr}zlist[Hashable]rr)ryr|rIr'rra)rF)rIr'rrarrrr )ryr|rIr'rrrra)rrrrarr?)vrD __future__r collectionsrrriorrrrtypingrr r r r r rnumpyr pandas._libsrpandas._libs.librpandas._libs.writersr pandas.errorsrrrrpandas.util._decoratorsrrpandas.util._exceptionsrpandas.core.dtypes.baserpandas.core.dtypes.commonrrrpandas.core.dtypes.dtypesrpandasrrrr r!r"r#pandas.core.framer$pandas.core.indexes.baser%pandas.core.indexes.ranger&pandas.core.seriesr'pandas.core.shared_docsr(pandas.io.commonr)collections.abcr*r+typesr,r-pandas._typingr.r/r0r1r2r3rs_statafile_processing_params1_statafile_processing_params2_chunksize_params_iterator_params _reader_notes_read_stata_docrhrgr rCr}rrrrrrrrrrHrrIteratorrrnrr0ryrrrrrcrergrrrFrrWrs  # (5 52 7(*0%0'$4!N !G$ "(    %&)==>?  ! "?8t      %&'(  !"$O dAq) U)]@h7V(uE #% % )yxvvr%O%>CCL\ \ ~|&+s|||&~ /!% ! $(# &--1!4!! !  !  !!"!!!!$!+!!!HD0C2 !GJGL*G*G(+*G?C*G*GZ !23$%:;gEK B+K B K B\'GT1rrjz[zz rnrr