pandas is built on top of NumPy and is intended to integrate well within a scientific computing environment with many other 3rd party libraries. Here are just a few of the things that pandas does well: month/quarter/year defined by the frequency of the DateTimeIndex / Timestamp (GH4565, GH6998) • Local variable usage has changed in pandas.eval()/DataFrame.eval()/DataFrame.query() (GH5987). For the DataFrame locals – Local variables must be referred to explicitly. This means that even if you have a local variable that is not a column you must still refer to it with the ’@’ prefix. – You can have an expression

. . . . . . . . . . . . . . . . . . . . . 396 12.3 Setting Startup Options in python/ipython Environment . . . . . . . . . . . . . . . . . . . . . . . . 397 12.4 Frequently Used Options . . . . . . pandas is built on top of NumPy and is intended to integrate well within a scientific computing environment with many other 3rd party libraries. Here are just a few of the things that pandas does well: 7 4 NaN 5 11 6 13 dtype: float64 • Added a DataFrame.round method to round the values to a variable number of decimal places (GH10568). In [49]: df = pd.DataFrame(np.random.random([3, 3]), columns=['A'

. . . . . . . . . . . . . . . . . . . . . 326 11.3 Setting Startup Options in python/ipython Environment . . . . . . . . . . . . . . . . . . . . . . . . 327 11.4 Frequently Used Options . . . . . . pandas is built on top of NumPy and is intended to integrate well within a scientific computing environment with many other 3rd party libraries. Here are just a few of the things that pandas does well: subplots=True may draw unnecessary minor xticks and yticks (GH7801) • Bug in StataReader which did not read variable labels in 117 files due to difference between Stata docu- mentation and implementation (GH7816)

. . . . . . . . . . . . . . . . . . . . . 318 11.3 Setting Startup Options in python/ipython Environment . . . . . . . . . . . . . . . . . . . . . . . . 319 11.4 Frequently Used Options . . . . . . pandas is built on top of NumPy and is intended to integrate well within a scientific computing environment with many other 3rd party libraries. Here are just a few of the things that pandas does well: subplots=True may draw unnecessary minor xticks and yticks (GH7801) • Bug in StataReader which did not read variable labels in 117 files due to difference between Stata docu- mentation and implementation (GH7816)

pandas is built on top of NumPy and is intended to integrate well within a scientific computing environment with many other 3rd party libraries. Here are just a few of the things that pandas does well: all of the open handles are 0. Essentially you have a local instance of HDFStore referenced by a variable. Once you close it, it will report closed. Other references (to the same file) will continue to accessed (GH3982, GH3985, GH4028, GH4054) • Series.hist will now take the figure from the current environment if one is not passed • Fixed bug where a 1xN DataFrame would barf on a 1xN mask (GH4071) • Fixed

. 331 3.3.5 Creating a development environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 332 3.3.6 Creating a Windows development environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 512 12.3 Setting Startup Options in python/ipython Environment . . . . . . . . . . . . . . . . . . . . . . . . 513 12.4 Frequently Used Options . . . . . . value_labels . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1121 pandas.io.stata.StataReader.variable_labels . . . . . . . . . . . . . . . . . . . . . . . . . . . 1121 pandas.io.stata.StataWriter.write_file

. 329 3.3.5 Creating a development environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 330 3.3.6 Creating a Windows development environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 510 12.3 Setting Startup Options in python/ipython Environment . . . . . . . . . . . . . . . . . . . . . . . . 511 12.4 Frequently Used Options . . . . . . value_labels . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1118 pandas.io.stata.StataReader.variable_labels . . . . . . . . . . . . . . . . . . . . . . . . . . . 1118 pandas.io.stata.StataWriter.write_file

. 379 3.3.5 Creating a development environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 380 3.3.6 Creating a Windows development environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 572 11.3 Setting Startup Options in python/ipython Environment . . . . . . . . . . . . . . . . . . . . . . . . 573 11.4 Frequently Used Options . . . . . . value_labels . . . . . . . . . . . . . . . . . . . . . . . 1219 34.1.12.5 pandas.io.stata.StataReader.variable_labels . . . . . . . . . . . . . . . . . . . . . . 1219 34.1.12.6 pandas.io.stata.StataWriter.write_file

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 407 3.3.4 Creating a development environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 407 3.3.4.1 Installing a C Complier . . . . . . . 408 3.3.4.2 Creating a Python Environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . 408 3.3.4.3 Creating a Python Environment (pip) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 600 11.3 Setting Startup Options in python/ipython Environment . . . . . . . . . . . . . . . . . . . . . . . . 601 11.4 Frequently Used Options . . . . . .

where ValueError is wrongly raised when calling count() method of a SeriesGroupBy when the grouping variable only contains NaNs and numpy version < 1.13 (GH21956). • Multiple bugs in pandas.core.window.Rolling this for you. The installer can be found here The next step is to create a new conda environment. A conda environment is like a virtualenv that allows you to specify a specific version of Python and set create -n name_of_my_env python This will create a minimal environment with only Python installed in it. To put your self inside this environment run: source activate name_of_my_env On Windows the command