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 3. Suppose you have a numpy array. arr = numpy.arange (10000).reshape (250,40) If you want to print the full array in a one-off way (without toggling np.set_printoptions), but want something simpler (less code) than the context manager, just do. for row in arr: print row. In recent IPython, you can just use display(df) if df is a panda dataframe, it will just work. On older version you might need to do a from IPython.display import display. It will also automatically display if the result of the last expression of a cell is a data_frame. For example this notebook. Of course the representation will depends on the Yes. There are several ways: Display the data frame in a cell output, then right-click on the output and select Create New View for Output. Use jupyterlab-sidecar package: from sidecar import Sidecar sc = Sidecar (title='My dataframe') with sc: display (df) (JupyterLab 3.3+) Activate the visual debugger, go to variables list, hover over the Hopefully this is automatically fixed once 1. and 2. are fixed (my other tables show full date + hours, etc without problem). This is what I have tried. I have used the following two lines to improve the printout somewhat: pd.set_option('display.max_columns', 20) pd.set_option('display.width', 2000) This gives a neat output, see below: The display function. All notebooks load a display function by default, which can be used to display the normal DataFrame from anywhere in the cell. This avoids the uglier output with the print function. display (bikes) 2 + 3. 5. The display function can output any number of objects vertically. You can visualize the content of this Spark dataframe by using display (sdf) function as show below: sdf = spark.sql("select * from default_qubole_airline_origin_destination limit 10") display(sdf) By default, the dataframe is visualized as a table. The following illustration shows the sample visualization chart of display (sdf). I’m still playing around with the UK’s COVID-19 vaccination data and in this blog post we’ll learn how to format a DataFrame that contains a mix of string and numeric values. Note On 10th November 2022 I created a video that covers the same content as this blog post. 7WYwb.