i have a python pygame program that simulates a racecar, driving and dodging blocks, this program worked 100% until i tried it today, now it gives me a error, the error is: this makes me think somethings wrong with the font i use, it is realy very frustrating, and i realy cant see anything wrong, here is my code: the
Convert month int to month name in Pandas
I want to transform an integer between 1 and 12 into an abbrieviated month name. I have a df which looks like: I want the df to look like this: Most of the info I found was not in python>pandas>dataframe hence the question. Answer You can do this efficiently with combining calendar.month_abbr and df[col].apply()
Pandas groupby and make set of items
I am using pandas groupby and want to apply the function to make a set from the items in the group. The following results in TypeError: ‘type’ object is not iterable: But the following works: In my understanding the two expression are similar, what is the reason why the first does not work? Answer Update As late as pandas version
How to call audio plugins from within Python?
I’ve noticed that some open source DAWs such as Ardour and Audacity are able to access audio plugins (e.g. VST, AU) that the user has installed on their system. This makes me think that “there ought to be a way” to do this in general. Specifically, I’d like to call some plugins from within my own audio-processing application, which I’m
Passing command line arguments to argv in jupyter/ipython notebook
I’m wondering if it’s possible to populate sys.argv (or some other structure) with command line arguments in a jupyter/ipython notebook, similar to how it’s done through a python script. For instance, if I were to run a python script as follows: python test.py False Then sys.argv would contain the argument False. But if I run a jupyter notebook in a
Why is statistics.mean() so slow?
I compared the performance of the mean function of the statistics module with the simple sum(l)/len(l) method and found the mean function to be very slow for some reason. I used timeit with the two code snippets below to compare them, does anyone know what causes the massive difference in execution speed? I’m using Python 3.5. The code above executes
Converting Pandas dataframe into Spark dataframe error
I’m trying to convert Pandas DF into Spark one. DF head: Code: And I got an error: Answer You need to make sure your pandas dataframe columns are appropriate for the type spark is inferring. If your pandas dataframe lists something like: And you’re getting that error try: Now, make sure .astype(str) is actually the type you want those columns
Using setuptools, how can I download external data upon installation?
I’d like to create some ridiculously-easy-to-use pip packages for loading common machine-learning datasets in Python. (Yes, some stuff already exists, but I want it to be even simpler.) What I’d like to achieve is this: User runs pip install dataset pip downloads the dataset, say via wget http://mydata.com/data.tar.gz. Note that the data does not reside in the python package itself,
Jupyter: disable restart kernel warning
I’m using jupyter 4.1.0, and I find myself making frequent use of the “Restart & Run All” feature. Every time I use that button it displays this warning: Is there a way to disable that warning? Answer You can add a cell in your notebook and using the following statements: And the kernel will restart immediately.
Pairing bluetooth devices with Passkey/Password in python – RFCOMM (Linux)
I am working on a Python script to search for bluetooth devices and connect them using RFCOMM. This devices has Passkey/Password. I am using PyBlueZ and, as far as I know, this library cannot handle Passkey/Password connections (Python PyBluez connecting to passkey protected device). I am able to discover the devices and retrieve their names and addresses: But if tried