I now know that I can output multiple charts from IPython pandas by embedding them in one plot space which will appear in a single output cell in the notebook.
Can I do something similar with Pandas HTML Tables?
I am getting data from multiple tabs (about 15-20) on a spreadsheet and running them though a set of regressions and I'd like to display the results together, perhaps 2 up.. But since the function to display the table only displays one, the last one, not sure how to approach. Ideas?
I'd even be happy to display in successive output cells.. not real sure how to do that either But I guess I could do something really dirty calling each (spreadsheet) tab in a separate cell.. Ughh... FWIW I'm on IPython 2.0 dev and Pandas 13
This does it:
area-tabs=list(map(str, range(1, 28))) # for all 27 tabs
#area_tabs=['1','2'] # for specific tabs
for area_tabs in area_tabs:
actdf,aname = get_data(area_tabs) #get_data gets the data and does a bunch or regression and table building
aname,actdf,merged2,mergederrs,montdist,ols_test,mergedfcst=projections(actdf)
IPython.display.display('Area: %s' % aname, mergederrs.tail(12))
IPython.display.display('Area: %s' % aname, ols_test)
IPython.display.display('Area: %s' % aname, merged2)
SO I can print all the results for each tab on the spreadsheet
Related
I am working on the Jupyter notebook and have been facing issues in increasing the length of the output of the Jupyter Notebook. I can see the output as follows:
I tried increasing the default length of the columns in pandas with no success. Can you please help me with it?
If you were using the typical way to view a dataframe in Jupyter (see my puzzelment about your screenshot in my comments to your original post) it would be things like this:
adapted from answer to 'Pretty-print an entire Pandas Series / DataFrame'
with pd.option_context('display.max_rows', None, 'display.max_columns', None):
display(df)
(Note that will work with the text-based viewing, too. Note it uses print(df) in the answer to 'Pretty-print an entire Pandas Series / DataFrame'.
Adjust the 'display.max_colwidth' if you want the entire column text to show:
with pd.option_context('display.max_rows', None, 'display.max_columns', None,'display.max_colwidth', -1):
display(df)
(If you prefer text like you posted, replace display() with print()
Generally with the solutions above the view window in Jupyter will get scrollbars so you can navigate to view all still.
You can also set the number of rows to show to be lower to save space, see example here.
You may also be interested in Pandas dataframe hide index functionality? or Using python / Jupyter Notebook, how to prevent row numbers from printing?.
As pointed out here, setting some some global options is covered in the Pandas Documentation for top-level options.
For display() to work these days you don't need to do anything extra. But if your are using old Jupyter or it doesn't work then try adding towards the top of your notebook file and running the following as a cell first:
from IPython.display import display
One question please.
I like to use rstudio to code in python and R, but when I print a pandas dataframe I get output that doesn't use all the space. It is not very friendly and it is worse if I have more variables.
As shown in the attached image.
Is there a way to display the columns to the right like we do with tibble in r?
Thanks!
I have tried using these options but it doesn't work.
pd.set_option('display.max_columns', None)
pd.set_option('display.width', None)
I am trying to represent cubic spline interpolation information for function f(x) as a dataframe.
When trying to print into a spyder, I find that the columns are being cut off. When trying to reproduce the output in Jupiter Lab, I got the same thing.
When I ran in ipython via terminal I got the desired full dataframe output.
I searched the integnet and tried the pandas commands setting options pd.set_options(), but nothing came of it.
I attach a screenshot with the output in ipython.
In Juputer can use:
from IPython.display import display, HTML
and instead of
print(dataframe)
use of in anyway place
display(HTML(dataframe.to_html()))
This will create a nice table.
Unfortunately, this will not work in the spyder. So you can try to adjust the width of the ipython were suggested. But in most cases this will make the output poorly or unreadable.
After trying the dataframe methods, I found what appears to be a cropping setting.
In Spyder I used:
pd.set_option('expand_frame_repr', False)
print(dataframe)
This method explains why increasing max_column didn't help me previously.
You can specify a maximum number for rows or columns using pd.set_options(display.max_columns=1000)
But you don't have to set an arbitrary value, but rather use None instead to make sure every size will be covered.
For rows, use:
pd.set_option('display.max_rows', None)
And for columns, use:
pd.set_option('display.max_columns', None)
It is a result of the display width. You can use the following set_options():
pd.set_options(display.width=1000) #make huge
You may also have to raise max columns but it should be smart enough to adjust automatically after you make width bigger:
pd.set_options(display.max_columns=None)
I want to do the following in a Jupyter Notebook:
Create a pyplot.figure in a cell;
For each subsequent cells, calculate values and plot them to that same figure without displaying anything;
At the end, in another cell, display the figure with the result of every previous plot command.
Currently, while using %matplotlib notebook, the figure is always displayed after the same cell it's been created, and I don't even call plt.show().
This is not the behavior I desire. Instead I would like to postpone the display of the figure for the last cell only, but the figure of course should contain the results of the sequential plot commands called in the cells in between.
You can capture the content of a cell of a jupyter notebook using the magic command %%capture. You can also hide any output of a specific line by putting a ; at the end of it.
Showing the figure can be done by simply typing the variable in which the figure is stored, e.g. fig.
Combining those techniques gives you
import matplotlib.pyplot as plt
%matplotlib notebook
%%capture captured
fig, ax=plt.subplots()
ax.plot([1,2,3]);
fig # now show the figure
which is probably more understandable in the acutal notebook like this:
Also see How to overlay plots from different cells?
I am using Ipython Notebook to generate some bar plots.
The code cell is this:
kcount =0;for k, v in pledge.groupby(['Date','Break']).sum().Amount.iteritems():
if k[0] <> kcount:
kcount=k[0]
pledge[pledge.Date==k[0]].groupby(['Break','Progcode'])['Amount'].sum().plot(kind='bar')
plt.title(k[0])
plt.figure()
This gives me a bar plot for every day of our pledge drive, showing how each show within that day did. 24 charts in all. They display great as output on the screen, but when I use the Print button in Ipython Notebook, it only prints enough graphs to fill the last page, which can vary from 3 to 6 graphs depending on the printer used. One printer used reported that it required 11x17 paper for the print job (not something I set anywhere) and when I manually set it for 8 1/2 x 11, it again only printed out the first 3 pages. I am at a loss as to what to do at this point.
As a workaround, can you can use plt.savefig('filename.png') (or .jpg, or .whatever) to save an image file and then print the files out manually?
I ended up saving these pages to a multipage PDF file and then printing them from there.
Consult the docs http://matplotlib.org/api/backend_pdf_api.html
To see how to save several figures to a multipage PDF file.
This also looks like a good resource. http://blog.marmakoide.org/?p=94