I want to create a table with Python that looks like a simple excel table, therefore I have already used the pyExcelerator. But now I thought about just using pyplot.table which seems to be very easy. However, I need to make some changes and I don't know if this is possible in vpyplot.table`.
For example I want to add a cell in the upper left corner and I also want to make two cells beneath the cell t+1 (see the table example below).
So, is it possible to do these changes in pyplot.table or should I better use another way to make tables?
Building a program to generate an table in a image for inclusion into your word document is a bit overkill. Its a lot of added work and completely unnecessary effort. Make the table in Excel and then paste it into Word. It'll look good and will be easier to update and change.
If you are using this as an excuse to learn something new, that is all well and good, but you need to give us more to help you with. SO isn't a code factory. Offer up what you have tried, and samples of code you are having trouble with. We can help with that.
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So, I am making a roguelike game using Python as my language. I am using NumPy and tcod currently for libraries, and I have been trying to figure out how I can take the procedurally generated map "cells," and append them to indexes within a NumPy array.
Context: I have followed the 2020 tcod tutorial found on the roguelikedev subreddit to get to the point I am at now (Here is a link to the source on GitHub. I have made only trivial changes to colors and such so far). I've coded simple stuff in Java before but never messed with Python much, nor have I ever tried something like this. In short, I feel a little lost.
Basically, I want to change the way the maps are generated. Currently, an area the size of the terminal is preocedurally generated, and when the player moves down some stairs, a new map is generated, and the old one is basically thrown away. The idea being that it's a dungeon. I don't want this. My goal is to have it be an open map, where the player can go North, South, East, or West.
This would require the engine to save the map (I assume to a list or an array or something), and keep updating it whenever the player moves to a new cell on the grid.
Now I'm not asking anyone to write the code for me, but I just can't seem to really wrap my head around how to go about actually doing this.
So far, my problem is I don't know exactly how to put the gamemaps onto a list. Should I make them entries within a dictionary? Use a list? Is what I'm trying to do even possible?
Figured I'd give this site a shot. Any help is appreciated.
I'm no sure what the right terminology to use for this ask is, but i want to create a python output that will look something like this:
With the intent of having some Data extracted from specific cells of a dataframe fill in the TEXT section of the image. Obviously i want the data to not be hard-coded so i can change it as per the topic. What packages even do this? I've never explored the "visual" component side of python before.
I am a novice at python so I apologize if this is confusing. I am trying to create a 6 variable venn diagram. I was trying to use matplotlib-venn, however the problem I am having is creating the sets is turning out to be impossible for me. My data is thousands of rows long with a unique index and each column has boolean values for each category. It looks something like this:
|A|B|C|D|E|F|
|0|0|1|0|1|1|
|1|1|0|0|0|0|
|0|0|0|1|0|0|
Ideally I'd like to make a venn diagram which would show that these # of people overlap with category A and B and C. How would I go about doing this? If anyone would be able to point me in the right direction, I'd be really grateful.
I found this person had a similiar problem with me and his solution at the end of that forum is what I'd like to end up at except with 6 variables: https://community.plotly.com/t/how-to-visualize-3-columns-with-boolean-values/36181/4
Thank you for any help!
Perhaps you might try to be more specific about your needs and what you have tried.
Making a six-set Venn diagram is not trivial at all, ever more so if you want to make the areas proportional. I made a program in C++ (nVenn) with a translation to R (nVennR) that can do that. I suppose it might be used from python, but I have never tried and I do not know if that is what you want. Also, interpreting six-set Venn diagrams is not easy, you may want to check upSet for a different kind of representation. In the meantime, I can point you to a web page I made that explains how nVenn works (link).
I have many files with three million lines in identical tab delimited format. All I need to do is divide the number in the 14th "column" by the number in the 12th "column", then set the number in the 14th column to the result.
Although this is a very simple function I'm actually really struggling to work out how to achieve this. I've spent a good few hours searching this website but unfortunately the answers I've seen have completely gone over the top of my head as I'm a novice coder!
The tools I have Notepad++ and Ultraedit (which has the ability to use Javascript, although i'm not familiar with this), and Python 3.6 (I have very basic Python knowledge). Other answers have suggested using something called "awk", but when I looked this up it needs Unix - I only have Windows. What's the best tool for getting this done? I'm more than willing to learn something new.
In python there are a few ways to handle csv. For your particular use case
I think pandas is what you are looking for.
You can load your file with df = pandas.read_csv(), then performing your division and replacement will be as easy as df[13] /= df[11].
Finally you can write your data back in csv format with df.to_csv().
I leave it to you to fill in the missing details of the pandas functions, but I promise it is very easy and you'll probably benefit from learning it for a long time.
Hope this helps
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I'm trying to take a 1.8mB txt file. There are couple of header lines afterwards its all space separated data. I can pull the data off using pandas. What I'm wanting to do with the data is:
1) Cut out the non essential data. ie the first 1675 lines, roughly I want to remove and the last 3-10 lines, varies day to day, I also want to remove. I can remove the first lines, kind of. The big problem with this idea I'm having right now is knowing for sure where the 1675 pointer location is. Using something like
df = df[df.year > 1978]
only moves the initial 'pointer' to 1675. If I try
dataf = df[df.year > 1978]
it just gives me a pure copy of what I would have with the first line. It still keeps the pointer to the same 1675 start point. It won't allow me to access any of the first 1675 rows but they are still obviously there.
df.year[0]
It comes back with an error suggesting row 0 doesn't exist. I have to go out and search to find what the first readable row is...instead of flat out removing the rows and moving the new pointer up to 0 it just moves the pointer to 1675 and won't allow access to anything lower than that. I still haven't found a way to be able to determine what the last row number is through programming, through the shell it's easy but I need to be able to do it through the program so I can set up the loop for point 2.
2) I want to be able to take averages of the data, 'x' day moving averages and create a new column with the new data once I have calculated the moving average. I think I can create the new column with the Series statement...I think...I haven't tried it yet though as I haven't been able to get this far yet.
3) After all this and some more math I want to be able to graph the data with a homemade graph. I think this should be easy once I have everything else completed. I have already created the sample graph and can plot the points/lines on the graph once I have the data to work with.
Is panda the right lib for the project or should I be trying to use something else? So far the more research I do...the more lost I get as everything I keep trying gets me a little further but sets me even further back at the same time. In something similar I saw mention using something else when wanting to do math on the data block. Their wasn't any indication as to what he used though.
It sounds like you main trouble is indexing. If you want to refer to the "first" thing in a DataFrame, use df.iloc[0]. But DataFrame indexes are really powerful regardless.
http://pandas.pydata.org/pandas-docs/stable/indexing.html
I think you are headed in the right direction. Pandas gives you nice, high level control over your data so that you can manipulate it much more easily than using traditional logic. It will take some work to learn. Work through their tutorials and you should be fine. But don't gloss over them or you'll miss some important details.
I'm not sure why you are concerned that the lines you want to ignore aren't being deleted as long as they aren't used in your analysis, it doesn't really matter. Unless you are facing memory constraints, it's probably irrelevant. But, if you do find you can't afford to keep them around, I'm sure there is a way to really remove them, even if it's a bit sideways.
Processing a few megabytes worth of data is pretty easy these days and Pandas will handle it without any problems. I believe you can easily pass pandas data to numpy for your statistical calculations. You should double check that, though, before taking my word for it. Also, they mention matplotlib on the pandas website, so I am guessing it will be easy to do basic graphing as well.