I want to have a checkbox (ipywidgets) alongside of my desired columns (pandas dataframe). So whenever there is an available check symbol in the box I want only those values to be present in my dataframe. I only can use ipywidgets and pandas dataframe. Briefly, my intentions could be visualized like in the figure below:
enter image description here
can somebody help me with this?
I had no problem with the alignment in the old version but when I upgraded to the new version I saw this happen. I tried the following 3 different approach below the dataframe but none of them fixes the problem. Is there any way to work around it?
#Sets df size with width 1000 and height 300, but width has a limited range
st.dataframe(df, 1000, 300)
st.dataframe(df, use_container_width=True)
st.write(df, use_container_width=True)
I ask this question for a while now but yet didn't get any response until I figured a way to handle my problem.
I used streamlit AgGrid Component to fix my problem. AgGrid() by default will center the dataframe, it also has other awesome features of handling data frames much better than st.dataframe() and it is pretty simple and clean. I could even choose to color the data frame to my liking which I found pretty cool and interactive.
In case you face similar problem and want to take this approach I will recommend you visit streamlit AgGrid Component to know the inside of the component and how it is implimented.
from st_aggrid import AgGrid
AgGrid(df)
OUTPUT:
I have a dataframe and I'm using PySpark, when I'm showing the data, it not showing very well, like the next image:
enter image description here
How can I fix it? Thank You.
There's not a whole lot you can do. The issue is with line wrap. A common workaround is to use pandas
df.limit(5).toPandas().head()
If you're using a Jupyter Notebook, you can read more choices here: pyspark show dataframe as table with horizontal scroll in ipython notebook
I want to make my display tables bigger so users can see the tables better when that are used in conjunction with Jupyter RISE (slide shows).
How do I do that?
I don't need to show more columns, but rather I want the table to fill up the whole width of the Jupyter RISE slide.
Any idea on how to do that?
Thanks
If df is a pandas.DataFrame object.
You can do:
df.style.set_properties(**{'max-width': '200px', 'font-size': '15pt'})
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.