I'm working in Jupyter Notebook and I've got a small df but one of the columns (series) has long strings in each row. I'd like to temporarily extend the maximum column width for this df. The problem I'm encountering is that when I use. with pd.option_context ('display.max_colwidth', 200): print (df) I would like to output all columns (there are 20 of them), but with the settings it turns out like this, it’s not beautiful .. Please tell me how to expand the output area so that all columns fit and do not cover each other. Working with columns. display all columns in Jupyter notebook. df. columns. Lists the names of all of the columns in the data frame. display specific columns in Jupyter notebook. df ['column_name'] df ['column_name1', 'column_name2', 'column_name3'] Display one specific column or multiple columns by calling on their names. Jupyter captures some keystrokes, so you will not be able to type the code below in. Just copy and paste, or just your editor: #notebook-container.container { width: 90%; } Change the width as you like, I find 90% looks nicer than 100%. But it is totally up to your eye. The singular form dtype is used to check the data type for a single column. And the plural form dtypes is for data frame which returns data types for all columns. Essentially: import pandas as pd df = pd.DataFrame ( {'A': [1,2,3], 'B': [True, False, False], 'C': ['a', 'b', 'c']}) df.A.dtype # dtype ('int64') df.B.dtype # dtype ('bool') df.C To show it im using code: df ['column_name'].value_counts () It show only some of it, 864 25 1040 16 912 14 848 12 894 12 .. 1285 1 1287 1 1288 1 1297 1 2053 1. is it possible to show all of the output. Because i need to see all of them? i saw tutorial on youtube with the same code, and jupyter able to show all of the output unlike mine. python. 60. try: pandas.set_option ('display.max_columns', None) but depending how many columns you have this is not a good idea. The data is being abbreviated because you have too many columns to fit practically on the screen. You might be better off saving to a .csv to inspect the data. df.to_csv ('myfile.csv') View: The “View” menu in Jupyter Notebook provides options to control the appearance and layout of your notebook interface, allowing you to customize its display to your preferences and needs. Insert: The “Insert” menu in Jupyter Notebook contains options for adding new cells and other elements to your notebook, allowing you to insert .

jupyter notebook display all columns