how it was built, the recipe for conda-forge's python-profiling package can be found here. But if you discover any problems with the package, or you need other details w.r.t. Using conda search -info (as you did) is also a good way to to figure out what's going on with the dependencies. That may give a clue about where the incompatibility comes from. Try installing its dependencies one at a time into your preferred environment (specifying versions) and see which one fails to install. If that fails, try this, just to see what it brings along with it: conda create -n testenv -c conda-forge pandas-profiling=2.8.0 python=3.7
#Conda install pandas install
To specify the exact version you're looking for, try one of the following: conda install -c conda-forge pandas-profiling=2.8Ĭonda install -c conda-forge pandas-profiling=2.8.0 In cases like this, it's likely that there is some incompatibility between the dependencies of your current environment and the dependencies of the new package ( pandas-profiling), at least according to the most recent version of the package.īut apparently conda was able to find an older version of the package that has looser requirements (possibly due to a bug in that old package's metadata), so it decided to give you that version instead. This was built for Python 2.7, but my conda is managing for version 3.7.6!ĭoes anyone have any insight into what's going on here and how I can upgrade to the latest build? I then investigated the builds with conda search pandas-profiling -info, which revealed the following about the 1.4.1_0 build that appeared to install: pandas-profiling 1.4.1 0įile name : pandas-profiling-1.4.2
#Conda install pandas how to
I'd like to upgrade, but, being the neophyte data scientist I am, I'm not familiar enough with conda as a package manager to either figure out why the latest build on conda-forge is 1.4.1 or how to upgrade, either via pip or conda (ideally via conda, for the sake of consistency). I'll likely be missing out on some significant functionality. Update PYTHONPATH environment variable such that it can find the PySpark and Py4J under. Ensure the SPARKHOME environment variable points to the directory where the tar file has been extracted. Pandas-profiling conda-forge/osx-64::pandas-profiling-1.4.1-0 After that, uncompress the tar file into the directory where you want to install Spark, for example, as below: tar xzvf spark-3.4.0-bin-hadoop3.tgz. The following NEW packages will be INSTALLED:
Pandas-profiling-1.4.1 | 0 39 KB conda-forge This is the text that returned on the command line: The following packages will be downloaded:
The current build of pandas-profiling is 2.8.0. I decided to install it using conda, and, as per the documentation, I input conda install -c conda-forge pandas-profiling on the command line. Pandas-profiling (appears to be) a delightful little package that improves on the pd.scribe() method.
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