same name and structure. In [3]: url = ('https://raw.github.com/pandas-dev' ...: '/pandas/master/pandas/tests/data/tips.csv') ...: In [4]: tips = pd.read_csv(url) In [5]: tips.head() Out[5]: total_bill read_csv(), which works similarly. In [5]: url = ('https://raw.github.com/pandas-dev/' ...: 'pandas/master/pandas/tests/data/tips.csv') ...: In [6]: tips = pd.read_csv(url) In [7]: tips.head() Out[7]: total_bill data set if presented with a url. In [5]: url = ('https://raw.github.com/pandas-dev' ...: '/pandas/master/pandas/tests/data/tips.csv') ...: In [6]: tips = pd.read_csv(url) (continues on next page)

Python data analysis toolkit, Release 0.12.0 • filepath_or_buffer: Either a string path to a file, url (including http, ftp, and s3 locations), or any object with a read method (such as an open file or • filepath_or_buffer : a VALID JSON string or file handle / StringIO. The string could be a URL. Valid URL schemes include http, ftp, s3, and file. For file URLs, a host is expected. For instance, a local parsers. New in version 0.12. The top-level read_html() function can accept an HTML string/file/url and will parse HTML tables into list of pandas DataFrames. Let’s look at a few examples. Note: read_html

and structure. In [3]: url = ( ...: "https://raw.github.com/pandas-dev" ...: "/pandas/master/pandas/tests/io/data/csv/tips.csv" ...: ) ...: In [4]: tips = pd.read_csv(url) In [5]: tips.head() Out[5]: works similarly. In [5]: url = ( ...: "https://raw.github.com/pandas-dev/" ...: "pandas/master/pandas/tests/io/data/csv/tips.csv" ...: ) ...: In [6]: tips = pd.read_csv(url) In [7]: tips.head() Out[7]: presented with a url. In [5]: url = ( ...: "https://raw.github.com/pandas-dev" ...: "/pandas/master/pandas/tests/io/data/csv/tips.csv" ...: ) ...: In [6]: tips = pd.read_csv(url) In [7]: tips.head()

and structure. In [3]: url = ( ...: "https://raw.github.com/pandas-dev" ...: "/pandas/master/pandas/tests/io/data/csv/tips.csv" ...: ) ...: In [4]: tips = pd.read_csv(url) In [5]: tips.head() Out[5]: works similarly. In [5]: url = ( ...: "https://raw.github.com/pandas-dev/" ...: "pandas/master/pandas/tests/io/data/csv/tips.csv" ...: ) ...: In [6]: tips = pd.read_csv(url) In [7]: tips.head() Out[7]: presented with a url. In [5]: url = ( ...: "https://raw.github.com/pandas-dev" ...: "/pandas/master/pandas/tests/io/data/csv/tips.csv" ...: ) ...: In [6]: tips = pd.read_csv(url) In [7]: tips.head()

strategies They can take a number of arguments: • filepath_or_buffer: Either a string path to a file, url (including http, ftp, and s3 locations), or any object with a read method (such as an open file or • filepath_or_buffer : a VALID JSON string or file handle / StringIO. The string could be a URL. Valid URL schemes include http, ftp, s3, and file. For file URLs, a host is expected. For instance, a local parsers. New in version 0.12.0. The top-level read_html() function can accept an HTML string/file/url and will parse HTML tables into list of pandas DataFrames. Let’s look at a few examples. 486 Chapter

strategies They can take a number of arguments: • filepath_or_buffer: Either a string path to a file, url (including http, ftp, and s3 locations), or any object with a read method (such as an open file or • filepath_or_buffer : a VALID JSON string or file handle / StringIO. The string could be a URL. Valid URL schemes include http, ftp, s3, and file. For file URLs, a host is expected. For instance, a local parsers. New in version 0.12.0. The top-level read_html() function can accept an HTML string/file/url and will parse HTML tables into list of pandas DataFrames. Let’s look at a few examples. Note: read_html

urllib.urlopen(url).read() 135 return read_csv(StringIO(lines), index_col=0, parse_dates=True)[::-1] 136 /Library/Frameworks/EPD64.framework/Versions/7.3/lib/python2.7/urllib.pyc in urlopen(url, data, proxies) proxies) 84 opener = _urlopener 85 if data is None: ---> 86 return opener.open(url) 87 else: 88 return opener.open(url, data) /Library/Frameworks/EPD64.framework/Versions/7.3/lib/python2.7/urllib.pyc return getattr(self, name)(url) 208 else: 209 return getattr(self, name)(url, data) /Library/Frameworks/EPD64.framework/Versions/7.3/lib/python2.7/urllib.pyc in open_http(self, url, data) 342 if realhost:

strategies They can take a number of arguments: • filepath_or_buffer: Either a string path to a file, URL (including http, ftp, and S3 locations), or any object with a read method (such as an open file or • filepath_or_buffer : a VALID JSON string or file handle / StringIO. The string could be a URL. Valid URL schemes include http, ftp, S3, and file. For file URLs, a host is expected. For instance, a local parsers. New in version 0.12.0. The top-level read_html() function can accept an HTML string/file/URL and will parse HTML tables into list of pandas DataFrames. Let’s look at a few examples. 23.3. HTML

strategies They can take a number of arguments: • filepath_or_buffer: Either a string path to a file, URL (including http, ftp, and S3 locations), or any object with a read method (such as an open file or • filepath_or_buffer : a VALID JSON string or file handle / StringIO. The string could be a URL. Valid URL schemes include http, ftp, S3, and file. For file URLs, a host is expected. For instance, a local parsers. New in version 0.12.0. The top-level read_html() function can accept an HTML string/file/URL and will parse HTML tables into list of pandas DataFrames. Let’s look at a few examples. 23.3. HTML

and structure. In [3]: url = ( ...: "https://raw.github.com/pandas-dev" ...: "/pandas/master/pandas/tests/io/data/csv/tips.csv" ...: ) ...: In [4]: tips = pd.read_csv(url) In [5]: tips Out[5]: total_bill Excel, you would download and then open the CSV. In pandas, you pass the URL or local path of the CSV file to read_csv(): In [5]: url = ( ...: "https://raw.github.com/pandas-dev" ...: "/pandas/master/p "/pandas/master/pandas/tests/io/data/csv/tips.csv" ...: ) ...: In [6]: tips = pd.read_csv(url) In [7]: tips Out[7]: total_bill tip sex smoker day time size 0 16.99 1.01 Female No Sun Dinner 2 1 10.34 1.66 Male No