able to create a faster specialized tool. • pandas will soon become a dependency of statsmodels, making it an important part of the statistical computing ecosystem in Python. • pandas has been used extensively 1.1.1 New features • New fixed width file reader, read_fwf • New scatter_matrix function for making a scatter plot matrix from pandas.tools.plotting import scatter_matrix scatter_matrix(df, alpha=0 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) 84 opener = _urlopener 85

Creating a Windows development environment . . . . . . . . . . . . . . . . . . . . . . . . 381 3.3.7 Making changes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 381 3 application you may be able to create a faster specialized tool. • pandas is a dependency of statsmodels, making it an important part of the statistical computing ecosystem in Python. • pandas has been used extensively 23 version of cython to avoid problems with character encodings (GH14699) • Switched the test framework to use pytest (GH13097) • Reorganization of tests directory layout (GH14854, GH15707). 1.3.4 Deprecations

Creating a Windows development environment . . . . . . . . . . . . . . . . . . . . . . . . 379 3.3.7 Making changes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 379 3 application you may be able to create a faster specialized tool. • pandas is a dependency of statsmodels, making it an important part of the statistical computing ecosystem in Python. • pandas has been used extensively 23 version of cython to avoid problems with character encodings (GH14699) • Switched the test framework to use pytest (GH13097) • Reorganization of tests directory layout (GH14854, GH15707). 1.2.4 Deprecations

application you may be able to create a faster specialized tool. • pandas is a dependency of statsmodels, making it an important part of the statistical computing ecosystem in Python. • pandas has been used extensively 23 version of cython to avoid problems with character encodings (GH14699) • Switched the test framework to use pytest (GH13097) • Reorganization of tests directory layout (GH14854, GH15707). 1.5.4 Deprecations \\\\\\\\\\\\\\Out[64]: array([1, 2, 3], dtype=int8) 1.8.1.12 pandas development API As part of making pandas API more uniform and accessible in the future, we have created a standard sub-package of pandas

application you may be able to create a faster specialized tool. • pandas is a dependency of statsmodels, making it an important part of the statistical computing ecosystem in Python. • pandas has been used extensively created by pandas is a matplotlib object. As Matplotlib provides plenty of options to customize plots, making the link between pandas and Matplotlib explicit enables all the power of matplotlib to the plot. "string2": Index(6, medium, shuffle, zlib(1)).is_csi=False} There is some performance degradation by making lots of columns into data columns, so it is up to the user to designate these. In addition, you cannot

application you may be able to create a faster specialized tool. • pandas is a dependency of statsmodels, making it an important part of the statistical computing ecosystem in Python. • pandas has been used extensively created by pandas is a matplotlib object. As Matplotlib provides plenty of options to customize plots, making the link between pandas and Matplotlib explicit enables all the power of matplotlib to the plot. "string2": Index(6, medium, shuffle, zlib(1)).is_csi=False} There is some performance degradation by making lots of columns into data columns, so it is up to the user to designate these. In addition, you cannot

application you may be able to create a faster specialized tool. • pandas is a dependency of statsmodels, making it an important part of the statistical computing ecosystem in Python. • pandas has been used extensively created by pandas is a matplotlib object. As Matplotlib provides plenty of options to customize plots, making the link between pandas and Matplotlib explicit enables all the power of matplotlib to the plot. "string2": Index(6, medium, shuffle, zlib(1)).is_csi=False} There is some performance degradation by making lots of columns into data columns, so it is up to the user to designate these. In addition, you cannot

application you may be able to create a faster specialized tool. • pandas is a dependency of statsmodels, making it an important part of the statistical computing ecosystem in Python. • pandas has been used extensively is invalid. Use header=None for no header or header=int or list-like of ints to specify the row(s) making up the column names 1.1. v0.17.0 (October 9, 2015) 21 pandas: powerful Python data analysis toolkit causing incorrect results when upcasting was required (GH9731) • Bug in FloatArrayFormatter where decision boundary for displaying “small” floats in decimal format is off by one order of magnitude for a

application you may be able to create a faster specialized tool. • pandas is a dependency of statsmodels, making it an important part of the statistical computing ecosystem in Python. • pandas has been used extensively created by pandas is a matplotlib object. As Matplotlib provides plenty of options to customize plots, making the link between pandas and Matplotlib explicit enables all the power of matplotlib to the plot. "string2": Index(6, mediumshuffle, zlib(1)).is_csi=False} There is some performance degradation by making lots of columns into data columns, so it is up to the user to designate these. In addition, you cannot

application you may be able to create a faster specialized tool. • pandas is a dependency of statsmodels, making it an important part of the statistical computing ecosystem in Python. • pandas has been used extensively created by pandas is a matplotlib object. As Matplotlib provides plenty of options to customize plots, making the link between pandas and Matplotlib explicit enables all the power of matplotlib to the plot. "string2": Index(6, mediumshuffle, zlib(1)).is_csi=False} There is some performance degradation by making lots of columns into data columns, so it is up to the user to designate these. In addition, you cannot