search
Search
Login
Unlock 100+ guides
menu
menu
web
search toc
close
Comments
Log in or sign up
Cancel
Post
account_circle
Profile
exit_to_app
Sign out
What does this mean?
Why is this true?
Give me some examples!
search
keyboard_voice
close
Searching Tips
Search for a recipe:
"Creating a table in MySQL"
Search for an API documentation: "@append"
Search for code: "!dataframe"
Apply a tag filter: "#python"
Useful Shortcuts
/ to open search panel
Esc to close search panel
to navigate between search results
d to clear all current filters
Enter to expand content preview
icon_star
Doc Search
icon_star
Code Search Beta
SORRY NOTHING FOUND!
mic
Start speaking...
Voice search is only supported in Safari and Chrome.
Navigate to

Pandas DataFrame | notna method

schedule Aug 11, 2023
Last updated
local_offer
PythonPandas
Tags
tocTable of Contents
expand_more
mode_heat
Master the mathematics behind data science with 100+ top-tier guides
Start your free 7-days trial now!

Pandas DataFrame.notna(~) method returns a boolean mask where True is set for non-missing values and False for NaNs.

Parameters

The method does not take any parameters.

Return value

A boolean mask where:

  • True represents non-NaN values

  • False represents NaNs.

Examples

Consider the following DataFrame:

df = pd.DataFrame({"A":[np.NaN,2], "B":[3,np.NaN]})
df
   A    B
0  NaN  3.0
1  2.0  NaN

To check for non-NaN values:

df.notna()
   A      B
0  False  True
1  True   False

Note that this is useful, for instance, if you want to know how many non-missing values there are in your DataFrame:

df.notna().values.sum()
2
robocat
Published by Isshin Inada
Edited by 0 others
Did you find this page useful?
thumb_up
thumb_down
Comment
Citation
Ask a question or leave a feedback...
thumb_up
0
thumb_down
0
chat_bubble_outline
0
settings
Enjoy our search
Hit / to insta-search docs and recipes!