Getting started¶
This very simple case-study is designed to get you up-and-running quickly with
statsmodels
. Starting from raw data, we will show the steps needed to
estimate a statistical model and to draw a diagnostic plot. We will only use
functions provided by statsmodels
or its pandas
and patsy
dependencies.
Loading modules and functions¶
After installing statsmodels and its dependencies, we load a few modules and functions:
In [1]: import statsmodels.api as sm
In [2]: import pandas
In [3]: from patsy import dmatrices
pandas builds on numpy
arrays to provide
rich data structures and data analysis tools. The pandas.DataFrame
function
provides labelled arrays of (potentially heterogenous) data, similar to the
R
“data.frame”. The pandas.read_csv
function can be used to convert a
comma-separated values file to a DataFrame
object.
patsy is a Python library for describing
statistical models and building Design Matrices using R
-like formulas.
Data¶
We download the Guerry dataset, a
collection of historical data used in support of Andre-Michel Guerry’s 1833
Essay on the Moral Statistics of France. The data set is hosted online in
comma-separated values format (CSV) by the Rdatasets repository.
We could download the file locally and then load it using read_csv
, but
pandas
takes care of all of this automatically for us:
In [4]: df = sm.datasets.get_rdataset("Guerry", "HistData", cache=True).data
---------------------------------------------------------------------------
gaierror Traceback (most recent call last)
/usr/lib/python3.7/urllib/request.py in do_open(self, http_class, req, **http_conn_args)
1316 h.request(req.get_method(), req.selector, req.data, headers,
-> 1317 encode_chunked=req.has_header('Transfer-encoding'))
1318 except OSError as err: # timeout error
/usr/lib/python3.7/http/client.py in request(self, method, url, body, headers, encode_chunked)
1228 """Send a complete request to the server."""
-> 1229 self._send_request(method, url, body, headers, encode_chunked)
1230
/usr/lib/python3.7/http/client.py in _send_request(self, method, url, body, headers, encode_chunked)
1274 body = _encode(body, 'body')
-> 1275 self.endheaders(body, encode_chunked=encode_chunked)
1276
/usr/lib/python3.7/http/client.py in endheaders(self, message_body, encode_chunked)
1223 raise CannotSendHeader()
-> 1224 self._send_output(message_body, encode_chunked=encode_chunked)
1225
/usr/lib/python3.7/http/client.py in _send_output(self, message_body, encode_chunked)
1015 del self._buffer[:]
-> 1016 self.send(msg)
1017
/usr/lib/python3.7/http/client.py in send(self, data)
955 if self.auto_open:
--> 956 self.connect()
957 else:
/usr/lib/python3.7/http/client.py in connect(self)
1383
-> 1384 super().connect()
1385
/usr/lib/python3.7/http/client.py in connect(self)
927 self.sock = self._create_connection(
--> 928 (self.host,self.port), self.timeout, self.source_address)
929 self.sock.setsockopt(socket.IPPROTO_TCP, socket.TCP_NODELAY, 1)
/usr/lib/python3.7/socket.py in create_connection(address, timeout, source_address)
706 err = None
--> 707 for res in getaddrinfo(host, port, 0, SOCK_STREAM):
708 af, socktype, proto, canonname, sa = res
/usr/lib/python3.7/socket.py in getaddrinfo(host, port, family, type, proto, flags)
747 addrlist = []
--> 748 for res in _socket.getaddrinfo(host, port, family, type, proto, flags):
749 af, socktype, proto, canonname, sa = res
gaierror: [Errno -2] Name or service not known
During handling of the above exception, another exception occurred:
URLError Traceback (most recent call last)
<ipython-input-4-cab9fdf84142> in <module>()
----> 1 df = sm.datasets.get_rdataset("Guerry", "HistData", cache=True).data
/build/statsmodels-IFPJo1/statsmodels-0.8.0/.pybuild/cpython3_3.7_statsmodels/build/statsmodels/datasets/utils.py in get_rdataset(dataname, package, cache)
288 "master/doc/"+package+"/rst/")
289 cache = _get_cache(cache)
--> 290 data, from_cache = _get_data(data_base_url, dataname, cache)
291 data = read_csv(data, index_col=0)
292 data = _maybe_reset_index(data)
/build/statsmodels-IFPJo1/statsmodels-0.8.0/.pybuild/cpython3_3.7_statsmodels/build/statsmodels/datasets/utils.py in _get_data(base_url, dataname, cache, extension)
219 url = base_url + (dataname + ".%s") % extension
220 try:
--> 221 data, from_cache = _urlopen_cached(url, cache)
222 except HTTPError as err:
223 if '404' in str(err):
/build/statsmodels-IFPJo1/statsmodels-0.8.0/.pybuild/cpython3_3.7_statsmodels/build/statsmodels/datasets/utils.py in _urlopen_cached(url, cache)
210 # not using the cache or didn't find it in cache
211 if not from_cache:
--> 212 data = urlopen(url).read()
213 if cache is not None: # then put it in the cache
214 _cache_it(data, cache_path)
/usr/lib/python3.7/urllib/request.py in urlopen(url, data, timeout, cafile, capath, cadefault, context)
220 else:
221 opener = _opener
--> 222 return opener.open(url, data, timeout)
223
224 def install_opener(opener):
/usr/lib/python3.7/urllib/request.py in open(self, fullurl, data, timeout)
523 req = meth(req)
524
--> 525 response = self._open(req, data)
526
527 # post-process response
/usr/lib/python3.7/urllib/request.py in _open(self, req, data)
541 protocol = req.type
542 result = self._call_chain(self.handle_open, protocol, protocol +
--> 543 '_open', req)
544 if result:
545 return result
/usr/lib/python3.7/urllib/request.py in _call_chain(self, chain, kind, meth_name, *args)
501 for handler in handlers:
502 func = getattr(handler, meth_name)
--> 503 result = func(*args)
504 if result is not None:
505 return result
/usr/lib/python3.7/urllib/request.py in https_open(self, req)
1358 def https_open(self, req):
1359 return self.do_open(http.client.HTTPSConnection, req,
-> 1360 context=self._context, check_hostname=self._check_hostname)
1361
1362 https_request = AbstractHTTPHandler.do_request_
/usr/lib/python3.7/urllib/request.py in do_open(self, http_class, req, **http_conn_args)
1317 encode_chunked=req.has_header('Transfer-encoding'))
1318 except OSError as err: # timeout error
-> 1319 raise URLError(err)
1320 r = h.getresponse()
1321 except:
URLError: <urlopen error [Errno -2] Name or service not known>
The Input/Output doc page shows how to import from various other formats.
We select the variables of interest and look at the bottom 5 rows:
In [5]: vars = ['Department', 'Lottery', 'Literacy', 'Wealth', 'Region']
In [6]: df = df[vars]
---------------------------------------------------------------------------
NameError Traceback (most recent call last)
<ipython-input-6-817b52d314c7> in <module>()
----> 1 df = df[vars]
NameError: name 'df' is not defined
In [7]: df[-5:]