I have a simple csv file with ten columns!
When I set the following option in the notebook and print my csv file (which is in a pandas dataframe) it doesn't print all the columns from left to right, it prints the first two, the next two underneath and so on.
I used this option, why isn't it working?
pd.option_context("display.max_rows",1,"display.max_columns",100)
Even this doesn't seem to work:
pandas.set_option('display.max_columns', None)
I assume you want to display your data in the notebook than the following options work fine for me (IPython 2.3):
import pandas as pd
from IPython.display import display
data = pd.read_csv('yourdata.txt')
Either directly set the option
pd.options.display.max_columns = None
display(data)
Or, use the set_option method you showed actually works fine as well
pd.set_option('display.max_columns', None)
display(data)
If you don't want to set this options for the whole script use the context manager
with pd.option_context('display.max_columns', None):
display(data)
If this doesn't help, you might give a minimal example to reproduce your issue.
You can also display all the data by asking pandas to return HTML markup, and then having IPython render the HTML table.
import pandas as pd
from IPython.display import HTML
data = pd.read_csv('yourdata.csv')
HTML(data.to_html())
Using IPython 3.0.0 and Python 3.4, I found that display(data) as described by #Jakob will render as a table with up/down and left/right scroll bars, but the table is still wider than the cell and some columns are off-screen to the right. To see all the data, one must collapse the cell - which adds scroll bars. Consequently you have a scrolling box in a scrolling box, which is not ideal as you have to shift focus between the doubled-up scroll bars to navigate all the way through the data.
Using the HTML method, you render the enormous table as-is without any scroll bars. This cell can then be collapsed down to show only a single vertical and horizontal bar, which is more user-friendly.
The caveat to using HTML is the table takes longer to render. I was only using a ~150x50 matrix and the speed difference was noticeable, but not inconvenient. If you have an enormous table, don't use this method to display the entire thing at once. That said, if you do have an enormous table, rendering the whole thing at once is obviously going to be a bad idea however you try to do it.
I found this question as one of the first hits on Google. In jupyter lab,
pandas.set_option("display.max_columns", None)
Now seems to work fine - my example was 32 columns, it used to be truncated and is not any more.
Related
Does anyone know how to make Pandas outputs display properly in VS Code Jupyter Notebooks?
As you can see in the image, the values for individual columns in the output of a Pandas DataFrame aren't aligned (whereas they are aligned if you use Jupyter Notebooks directly on a web browser).
Click on the 3 dotted lines highlighted in the image above. From there its going to prompt you to select text or html. Click HTML, and the full data frame should show up
For the alignment of pandas, I think I have a relatively simple strategy. We can use IPython module.Use the following code to output the results.
from IPython.display import display
display(df2)
I think you've got a bracket mismatch. Change your code to this:
df2.loc[df2['Airport'] == 'ATL', ['Delay']]
Suppose I have a dataset with 100k rows (1000 different times, 100 different series, an observation for each, and auxilliary information). I'd like to create something like the following:
(1) first panel of plot has time on x axis, and average of the different series (and standard error) on y axis.
(2) based off the time slice (vertical line) we hover over in panel 1, display a (potentially down sampled) scatter plot of auxilliary information versus the series value at that time slice.
I've looked into a few options for this: (1) matplotlib + ipywidgets doesn't seem to handle it unless you explicitly select points via a slider. This also doesn't translate well to html exporting. This is not ideal, but is potentially workable. (2) altair - this library is pretty sleek, but from my understanding, I need to give it the whole dataset for it to handle the interactions, but it also can't handle more than 5kish data points. This would preclude my use case, correct?
Any suggestions as to how to proceed? Is what I'm asking impossible in the current state of things?
You can work with datasets larger than 5k rows in Altair, as specified in this section of the docs.
One of the most convenient solutions in my opinion is to install altair_data_server and then add alt.data_transformers.enable('data_server') on the top of your notebooks and scripts. This server will provide the data to Altair as long as your Python process is running so there is no need to include all the data as part of the created chart specification, which means that the 5k error will be avoided. The main drawback is that it wont work if you export to a standalone HTML because you rely on being in an environment where the server Python process is running.
This is a really basic question but I haven't been able to find an answer:
In Jupyter, if I execute two pandas df.describe() calls in the same cell, only the last one's output is displayed. The same is true for .info(), .head() etc. etc.
How do I persuade Jupyter and pandas to display all N of the above outputs sequentially as intended, with the same tabular formatting that is the default for a single output?
FWIW example code would be:
df1.describe()
#...
df2.describe()
dfN.describe() # Only the result of the final call is displayed
Points from comments addressed:
print(df1.describe()) works, but does not render the table identically to how it is rendered by describe() itself.
Displaying two pandas tables side-by-side (Jupyter notebook display two pandas tables side by side) may work, but doesn't scale to N tables.
You can configure your current session and specify what values to show by InteractiveShell.ast_node_interactivity:
%config InteractiveShell.ast_node_interactivity = 'all'
I want to display two images, that I have them saved locally, in one single makedown cell side-by-side? I found previous post but it uses HTML() not Image() method.
The way I tried was:
from IPython.core.display import Image, display
display(Image('/whateverfile/counts1.png',width=100,height=100), Image('/whateverfile/counts2',width=100, height=100))
But that did not work.
Any ideas how to solve this?
Thanks
from IPython.display import HTML, display
display(HTML("<table><tr><td><img src='/image/counts1.png'></td><td><img src='/image/counts2'></td></tr></table>"))
Set other parameters as you like.
Or maybe using nbextensions and splitting the cell in two (having 2 outputs side by side) would fit your needs?
I have to display a table with multiple columns but only a single row. Displaying it in the normal way using wxGrid doesnt look appealing at all and makes it hard for the user to read. I want to know if there is any way in which I can flip the table and display its contents vertically? Also is there any other way to make the data more presentable?
Just label the rows with the column names and the make one column. Then you could scroll through it that way. You just need to call SetRowLabelValue(rowNum, label). You may find this tutorial helpful (see the end): http://www.blog.pythonlibrary.org/2010/04/04/wxpython-grid-tips-and-tricks/
You could use a ListBox, but then you'd lose the label information.