Python | Pandas dataframe.notnull()

25 Aug, 2021
Python is a great language for doing data analysis, primarily because of the fantastic ecosystem of data-centric python packages. Pandas is one of those packages and makes importing and analyzing data much easier.Pandas dataframe.notnull() function detects existing/ non-missing values in the dataframe. The function returns a boolean object having the same size as that of the object on which it is applied, indicating whether each individual value is a na value or not. All of the non-missing values gets mapped to true and missing values get mapped to false. Note : Characters such as empty strings ” or numpy.inf are not considered NA values. (unless you set pandas.options.mode.use_inf_as_na = True). 
Syntax: DataFrame.notnull()Returns : Mask of bool values for each element in DataFrame that indicates whether an element is not an NA value. 
Example #1: Use notnull() function to find all the non-missing value in the dataframe. 
Python3
# importing pandas as pdimport pandas as pd # Creating the first dataframedf = pd.DataFrame({"A":[14, 4, 5, 4, 1],                   "B":["Sam", "olivia", "terica", "megan", "amanda"],                   "C":[20 + 5j, 20 + 3j, 7, 3, 8],                   "D":[14, 3, 6, 2, 6]}) # Print the dataframedf
Let’s use the dataframe.notnull() function to find all the non-missing values in the dataframe.  
Python3
# find non-na valuesdf.notnull()
Output :  
As we can see in the output, all the non-missing values in the dataframe has been mapped to true. There is no false value as there is no missing value in the dataframe  Example #2: Use notnull() function to find the non-missing values, when there are missing values in the dataframe. 
Python3
# importing pandas as pdimport pandas as pd # Creating the dataframedf = pd.DataFrame({"A":["Sandy", "alex", "brook", "kelly", np.nan],                   "B":[np.nan, "olivia", "terica", "", "amanda"],                   "C":[20 + 5j, 20 + 3j, 7, None, 8],                    "D":[14.8, 3, None, 2.3, 6]}) # find non-missing valuesdf.notnull()
Output :  
Notice, the empty string also got mapped to true indicating that it is not a NaN value.  
Python | Pandas dataframe.notnull() | GeeksforGeeks - YouTubeGeeksforGeeks532K subscribersPython | Pandas dataframe.notnull() | GeeksforGeeksWatch laterShareCopy linkInfoShoppingTap to unmuteIf playback doesn't begin shortly, try restarting your device.You're signed outVideos you watch may be added to the TV's watch history and influence TV recommendations. To avoid this, cancel and sign in to YouTube on your computer.CancelConfirmMore videosMore videosSwitch cameraShareInclude playlistAn error occurred while retrieving sharing information. Please try again later.Watch on0:000:000:00 / 3:20•Live•<div class="player-unavailable"><h1 class="message">An error occurred.</h1><div class="submessage"><a href="https://www.youtube.com/watch?v=YpXUoVnG1is" target="_blank">Try watching this video on www.youtube.com</a>, or enable JavaScript if it is disabled in your browser.</div></div>
 
sagartomar9927
Python pandas-dataFrame
Python pandas-dataFrame-methods
Python-pandas
Python
Writing code in comment?
Please use ide.geeksforgeeks.org,
generate link and share the link here.