Pandas on Jupyter Notebook VS Code not displaying outputs properly - python

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']]

Related

How do I display more than one pandas describe() output in a single jupyter cell?

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'

Why does pandas hide columns during display? [duplicate]

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.

ggplot not showing inside ipython notebook output area, rather popping up

I'm using IPython notebooks to save my results and perhaps to share code including graphics. I am using ggplot right now. But I cannot get ggplot to plot inside the notebook output area. It always gives me a pop-up window that shows the plot. I don't know how to save it along with the notebook easily. Is there something I need to configure to make that happen? "%matplotlib inline" I saw in a ggplot tutorial that below code should do it. What am I missing?
My code:
plot = ggplot(my_dataframe, aes("x")) + geom_histogram()
print plot
I got my answer elsewhere. It worked like a charm!
%pylab inline

resize ipython notebook output window with pandas dataframe output

As I learned here, there is an extension for the IPython notebook, that lets you specify the number of lines that are plotted before enabling scroll bars on the output cell. This does not work for Pandas data frames, because the div inside the .output_subarea has the style
max-height:1000px;max-width:1500px;overflow:auto;
even if I set the AutoScrollLimit to no-scroll. How to plot the data frames always without scroll bars?
This was changed for 0.16.2, see here
For ipython >= 3.0.0 will now use the notebook display controls

Image is produced in the editor, but not interactively in iPython

I am using seaborn which is a library based on matplotlib and that enhances some styling features of matplotlib.
If I write the following script in the editor and run it, I get the graph correctly displayed in the image file.
import seaborn as sns
sns.plt.plot([2,4,8,16],[1,2,3,4])
sns.plot.gcf()
sns.plot.savefig("C:\\in\\Fig1.png")
The problem is that when I write those same lines the interactive way in iPython one by one, I get a blank image file. However, the image is correctly displayed in iPython as soon as I execute the second line:
sns.plt.plot([2,4,8,16],[1,2,3,4])
So, the question is: why is this happening in the first place, and how do I get an image file with the graph inside it by using iPython?

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