#Miniconda vs anaconda upgrade
For some reason, a certain Scikit-learn function doesn’t work anymore.Īnd after a lot of digging, we find out that the error occurs because of the upgrade of NumPy.
#Miniconda vs anaconda code
But now, all of a sudden, the code breaks and we get an error message. So, we go back to it and try to run the code again. Then, when we are done with the data analysis project, we suddenly have an idea how we might approach our machine learning project differently.
#Miniconda vs anaconda install
So, we install it.Īnd because pandas depends on a newer version of NumPy, let’s say that the package manager upgrades Numpy from version 1.11.0 to 1.13.3. Let’s say we start working on a machine learning project and we install Scikit-learn with our package manager.Īfter a while, we get stuck and abandon the project to start a data analysis project. So, that’s why a package manager is useful.īut Conda is not just a package manager. So, it can become pretty complex to manually figure out all the right dependencies to make everything work.
Scikit-learn together with Pandas.Īnd that’s because the libraries might rely on the same dependency/dependencies (in this case NumPy) but with different versions. And that’s exactly what a package manager does.Īnd this becomes especially helpful when we want to use not just one specific library, but a couple of libraries, e.g. So, if we would have to do all that manually, then this could become quite cumbersome and time-consuming.Ī more convenient approach would be to simply specify the library that we want to use, in this case Scikit-learn, and then let a program figure out all the respective dependencies, that we need to install, to be able to actually use Scikit-learn. And on top of that, we need to install the right versions of all these packages/libraries (and let’s say we install the minimum requirements of these packages, so 0.17.0 and 1.11.0 respectively). So, if we want to use Scikit-learn, then we first need to install its dependencies, SciPy and NumPy in this case, and then also the respective dependencies of those dependencies. And those, in turn, have their own dependencies. In that case, we can’t just install the latest version of Scikit-learn (currently: 0.21.3) and start coding on our project.Īnd that’s because Scikit-learn depends on other libraries, for example SciPy and NumPy. bash_profile and make sure PATH is right.Let’s say we want to do a machine learning project and we want to use Scikit-learn for that. Go to Control Panel\System and Security\System\Advanced System Settings\Environment VariablesĪnd check path values, your user variable should contain DocsĬonda install -c anaconda pandas-datareaderĬonda is a package manager, just like pip, is used for updating Anaconda packages.Ĭonda is not recognized as internal or external command. Pandas-datareader extracts data from various Internet sources into a pandas DataFrame. Use Graphical installer to install Anaconda powered by Python 3.6 Anaconda comes with distribution of Python and R and includes over 100 of the most popular Python, R and Scala packages for data science. Anaconda is an open data science platform powered by Python.
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