|
126 | 126 | Return StataReader object for iterations, returns chunks with
|
127 | 127 | given number of lines."""
|
128 | 128 |
|
129 |
| -_iterator_params = """\ |
130 |
| -iterator : bool, default False |
131 |
| - Return StataReader object.""" |
132 |
| - |
133 | 129 | _reader_notes = """\
|
134 | 130 | Notes
|
135 | 131 | -----
|
|
138 | 134 | file is associated to an incomplete set of value labels that only
|
139 | 135 | label a strict subset of the values."""
|
140 | 136 |
|
141 |
| -_read_stata_doc = f""" |
142 |
| -Read Stata file into DataFrame. |
143 |
| -
|
144 |
| -Parameters |
145 |
| ----------- |
146 |
| -filepath_or_buffer : str, path object or file-like object |
147 |
| - Any valid string path is acceptable. The string could be a URL. Valid |
148 |
| - URL schemes include http, ftp, s3, and file. For file URLs, a host is |
149 |
| - expected. A local file could be: ``file://localhost/path/to/table.dta``. |
150 |
| -
|
151 |
| - If you want to pass in a path object, pandas accepts any ``os.PathLike``. |
152 |
| -
|
153 |
| - By file-like object, we refer to objects with a ``read()`` method, |
154 |
| - such as a file handle (e.g. via builtin ``open`` function) |
155 |
| - or ``StringIO``. |
156 |
| -{_statafile_processing_params1} |
157 |
| -{_statafile_processing_params2} |
158 |
| -{_chunksize_params} |
159 |
| -{_iterator_params} |
160 |
| -{_shared_docs["decompression_options"] % "filepath_or_buffer"} |
161 |
| -{_shared_docs["storage_options"]} |
162 |
| -
|
163 |
| -Returns |
164 |
| -------- |
165 |
| -DataFrame, pandas.api.typing.StataReader |
166 |
| - If iterator or chunksize, returns StataReader, else DataFrame. |
167 |
| -
|
168 |
| -See Also |
169 |
| --------- |
170 |
| -io.stata.StataReader : Low-level reader for Stata data files. |
171 |
| -DataFrame.to_stata: Export Stata data files. |
172 |
| -
|
173 |
| -{_reader_notes} |
174 |
| -
|
175 |
| -Examples |
176 |
| --------- |
177 |
| -
|
178 |
| -Creating a dummy stata for this example |
179 |
| -
|
180 |
| ->>> df = pd.DataFrame({{'animal': ['falcon', 'parrot', 'falcon', 'parrot'], |
181 |
| -... 'speed': [350, 18, 361, 15]}}) # doctest: +SKIP |
182 |
| ->>> df.to_stata('animals.dta') # doctest: +SKIP |
183 |
| -
|
184 |
| -Read a Stata dta file: |
185 |
| -
|
186 |
| ->>> df = pd.read_stata('animals.dta') # doctest: +SKIP |
187 |
| -
|
188 |
| -Read a Stata dta file in 10,000 line chunks: |
189 |
| -
|
190 |
| ->>> values = np.random.randint(0, 10, size=(20_000, 1), dtype="uint8") # doctest: +SKIP |
191 |
| ->>> df = pd.DataFrame(values, columns=["i"]) # doctest: +SKIP |
192 |
| ->>> df.to_stata('filename.dta') # doctest: +SKIP |
193 |
| -
|
194 |
| ->>> with pd.read_stata('filename.dta', chunksize=10000) as itr: # doctest: +SKIP |
195 |
| ->>> for chunk in itr: |
196 |
| -... # Operate on a single chunk, e.g., chunk.mean() |
197 |
| -... pass # doctest: +SKIP |
198 |
| -""" |
199 |
| - |
200 |
| -_read_method_doc = f"""\ |
201 |
| -Reads observations from Stata file, converting them into a dataframe |
202 |
| -
|
203 |
| -Parameters |
204 |
| ----------- |
205 |
| -nrows : int |
206 |
| - Number of lines to read from data file, if None read whole file. |
207 |
| -{_statafile_processing_params1} |
208 |
| -{_statafile_processing_params2} |
209 |
| -
|
210 |
| -Returns |
211 |
| -------- |
212 |
| -DataFrame |
213 |
| -""" |
214 |
| - |
215 | 137 | _stata_reader_doc = f"""\
|
216 | 138 | Class for reading Stata dta files.
|
217 | 139 |
|
|
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