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)
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
So, I have a pandas data frame with two fields
partition
account_list
1
[id1,id2,id3,...]
2
[id4,id6,id5,...]
since the list is quite long and I want to see the complete content I'm using
pd.set_option('display.max_rows', None)
pd.set_option('display.max_columns', None)
pd.set_option('display.width', None)
pd.set_option('display.max_colwidth', -1)
louvain_communities.limit(tot_communities).toPandas()
nevertheless, as you can see (Jupiter I think) still truncate the column (I had to edit out the data for privacy)
Is there a way to fix this? I really need to check have the complete list, not truncated, to be shown.
max_colwidth and max_seq_items together work. Code below synthesises list with 500 items. Change the range() and you can test however many you want.
import pandas as pd
pd.set_option("max_colwidth", None)
pd.set_option("max_seq_items", None)
pd.DataFrame([{"partition":i, "account_list":[f"id{j}" for j in range(500)]} for i in range(2)])
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'm trying to recreate the first panel.interact example in the Holoviz tutorial using a Pandas dataframe instead of a Dask dataframe. I get the slider, but the pandas dataframe row does not show.
See the original example at: http://holoviz.org/tutorial/Building_Panels.html
I've tried using Dask as in the Holoviz example. Dask rows print out just fine, but it demonstrates that panel seem to treat Dask dataframe rows differently for printing than Pandas dataframe rows. Here's my minimal code:
import pandas as pd
import panel
l1 = ['a','b','c','d','a','b']
l2 = [1,2,3,4,5,6]
df = pd.DataFrame({'cat':l1,'val':l2})
def select_row(rowno=0):
row = df.loc[rowno]
return row
panel.extension()
panel.extension('katex')
panel.interact(select_row, rowno=(0, 5))
I've included a line with the katex extension, because without it, I get a warning that it is needed. Without it, I don't even get the slider.
I can call the select_row(rowno=0) function separately in a Jupyter cell and get a nice printout of the row, so it appears the function is working as it should.
Any help in getting this to work would be most appreciated. Thanks.
Got a solution. With Pandas, loc[rowno:rowno] returns a pandas.core.frame.DataFrame object of length 1 which works fine with panel while loc[rowno] returns a pandas.core.series.Series object which does not work so well. Thus modifying the select_row() function like this makes it all work:
def select_row(rowno=0):
row = df.loc[rowno:rowno]
return row
Still not sure, however, why panel will print out the Dataframe object and not the Series object.
Note: if you use iloc, then you use add +1, i.e., df.iloc[rowno:rowno+1].
By default, the number of columns displayed by pandas commands is limited to display.max_columns. Is there something like df.showall() that can be used to override this on a per-command bases?
The simplest way I have found to do this is the following:
from IPython.core.display import HTML
HTML(df.to_html())
This will display the whole table in the IPython notebook output cell - all rows and columns. Scrollbars will appear for large tables.
To display all columns but no more than N rows, use:
HTML(df.head(N).to_html())
You can define a context manager:
from contextlib import contextmanager
#contextmanager
def temp_option(option, value):
old_value = pd.get_option(option)
pd.set_option(option, value)
yield
pd.set_option(option, old_value)
Then do what you want, something like
>>>with temp_option('display.max_rows', 200):
print(df)
I thought pandas already had this feature, but I couldn't find it.