df = df.replace({np.nan: None})
Note: For pandas versions <1.4, this changes the dtype of all affected columns to object.
To avoid that, use this syntax instead:
df = df.replace(np.nan, None)
Note 2: If you don't want to import numpy, np.nan can be replaced with native float('nan'):
df = df.replace({float('nan'): None})
Credit goes to this guy here on this Github issue, Killian Huyghe's comment and Matt's answer.
Answer from EliadL on Stack Overflow Top answer 1 of 16
398
df = df.replace({np.nan: None})
Note: For pandas versions <1.4, this changes the dtype of all affected columns to object.
To avoid that, use this syntax instead:
df = df.replace(np.nan, None)
Note 2: If you don't want to import numpy, np.nan can be replaced with native float('nan'):
df = df.replace({float('nan'): None})
Credit goes to this guy here on this Github issue, Killian Huyghe's comment and Matt's answer.
2 of 16
337
For pandas > 1.3.0 see this answer.
@bogatron has it right, you can use where, it's worth noting that you can do this natively in pandas:
df1 = df.where(pd.notnull(df), None)
Note: this changes the dtype of all columns to object.
Example:
In [1]: df = pd.DataFrame([1, np.nan])
In [2]: df
Out[2]:
0
0 1
1 NaN
In [3]: df1 = df.where(pd.notnull(df), None)
In [4]: df1
Out[4]:
0
0 1
1 None
Note: what you cannot do recast the DataFrames dtype to allow all datatypes types, using astype, and then the DataFrame fillna method:
df1 = df.astype(object).replace(np.nan, 'None')
Unfortunately neither this, nor using replace, works with None see this (closed) issue.
As an aside, it's worth noting that for most use cases you don't need to replace NaN with None, see this question about the difference between NaN and None in pandas.
However, in this specific case it seems you do (at least at the time of this answer).
Pandas
pandas.pydata.org › docs › reference › api › pandas.DataFrame.fillna.html
pandas.DataFrame.fillna — pandas 3.0.2 documentation
For non-object dtype, value=None will use the NA value of the dtype. See more details in the Filling missing data section. ... >>> df = pd.DataFrame( ... [ ... [np.nan, 2, np.nan, 0], ... [3, 4, np.nan, 1], ... [np.nan, np.nan, np.nan, np.nan], ... [np.nan, 3, np.nan, 4], ... ], ... columns=list("ABCD"), ... ) >>> df A B C D 0 NaN 2.0 NaN 0.0 1 3.0 4.0 NaN 1.0 2 NaN NaN NaN NaN 3 NaN 3.0 NaN 4.0 · Replace all NaN elements with 0s.
I need to replace NaN in one column with value for other col
I've seen this come up before. You want to use np.where. data['Grade'] = np.where(data['Grade'].isna(),data['Score'],data['Grade']) here's an example that sets null values in grade to values in score, and if it's not null, leaves the current value. More on reddit.com
10
1
July 15, 2021BUG: Replacing NaN with None in Pandas 1.3 does not work
I have checked that this issue has not already been reported. I have confirmed this bug exists on the latest version of pandas. (optional) I have confirmed this bug exists on the master branch of p... More on github.com
10
July 7, 2021BUG: dataframe.replace({np.nan: None}) failed when replaced even number of times
It should consistently have the ... no np.nan, doesn't matter how many replace attempts have been made. commit : 945c9ed python : 3.8.12.final.0 python-bits : 64 OS : Linux OS-release : 4.18.0-240.1.1.el8_3.x86_64 Version : #1 SMP Fri Oct 16 13:36:46 EDT 2020 machine : x86_64 processor : x86_64 byteorder : little LC_ALL : None LANG : None LOCALE : en_US.UTF-8 · pandas : 1.3.4 numpy ... More on github.com
6
November 16, 2021Replace None with NaN in pandas dataframe - Stack Overflow
Just double-checked it, it does work for me. Do you get any errors or the 'None' values don't get replaced? 2018-04-30T00:35:08.817Z+00:00 ... NB: this method uses np.nan, which has a float dtype (e.g.: float64), as opposed to pandas's default dtype of object for a nan column. More on stackoverflow.com
Statology
statology.org › home › pandas: how to replace nan with none
Pandas: How to Replace NaN with None
December 1, 2022 - This tutorial explains how to replace NaN values with a None value in a pandas DataFrame, including an example.
IARP
iarp.github.io › python › pandas-replace-nan-nat-with-none.html
Pandas replace all NaN and NaT values with None | IARP
View On GitHub · GitHub Profile · Pandas replace all NaN and NaT values with None · data.replace({pandas.NaT: None}, inplace=True) · Hosted on GitHub Pages using the Dinky theme
GeeksforGeeks
geeksforgeeks.org › python › replacing-pandas-or-numpy-nan-with-a-none-to-use-with-mysqldb
Replacing Pandas or Numpy Nan with a None to use with MysqlDB - GeeksforGeeks
July 23, 2025 - The resulting DataFrame 'replaced_df' contains 'None' in place of 'NaN' values. ... import pandas as pd import numpy as np df = pd.DataFrame({'A': [1, np.nan,3], 'B': [np.nan, 5, 6], 'C': [7, 8, np.nan]}) replaced_df = df.replace({np.nan: None}) print(replaced_df)
GeeksforGeeks
geeksforgeeks.org › python › replace-nan-with-blank-or-empty-string-in-pandas
Replace NaN with Blank or Empty String in Pandas? - GeeksforGeeks
July 23, 2025 - This function will replace an empty string inplace of the NaN value. ... # import pandas module import pandas as pd # import numpy module import numpy as np # create dataframe with 3 columns data = pd.DataFrame({ "name": ['sravan', np.nan, 'harsha', 'ramya'], "subjects": [np.nan, 'java', np.nan, 'html/php'], "marks": [98, np.nan, np.nan, np.nan] }) # replace nan with empty string # using replace() function data.replace(np.nan, '')
Reddit
reddit.com › r/learnpython › i need to replace nan in one column with value for other col
r/learnpython on Reddit: I need to replace NaN in one column with value for other col
July 15, 2021 -
I've been working on learning Python and for something to code, I picked some VBA that I had.
In VBA:
If Cells(I, "C").Value <> "" And Cells(I, "B").Value = "" Then
Cells(I, "B").Value = Cells(I, "C").Value
End IfIt simply checks if colC is not Null and colB is Null, then replaces colB with the value from colC.
I can read in the csv file, I was able to select and delete some rows I didn't want, but I can't seem to get the syntax right for this...
Top answer 1 of 5
2
I've seen this come up before. You want to use np.where. data['Grade'] = np.where(data['Grade'].isna(),data['Score'],data['Grade']) here's an example that sets null values in grade to values in score, and if it's not null, leaves the current value.
2 of 5
2
You should use the fillna method df["B"] = df["B"].fillna(df["C"])
Spark By {Examples}
sparkbyexamples.com › home › pandas › pandas replace nan with blank/empty string
Pandas Replace NaN with Blank/Empty String - Spark By {Examples}
November 19, 2024 - By using replace() or fillna() methods you can replace NaN values with Blank/Empty string in Pandas DataFrame. NaN stands for Not A Nuber and is one of the common ways to represent the missing data value in Python/Pandas DataFrame.
GitHub
github.com › pandas-dev › pandas › issues › 42423
BUG: Replacing NaN with None in Pandas 1.3 does not work · Issue #42423 · pandas-dev/pandas
July 7, 2021 - >>> import pandas as pd >>> import numpy as np >>> df = pd.DataFrame([0.5, np.nan]) >>> df.where(pd.notnull(df), None) 0 0 0.5 1 NaN · Replacing NaN values with None (or any other Python object) should work as in previous Pandas versions. >>> import pandas as pd >>> import numpy as np >>> df = pd.DataFrame([0.5, np.nan]) >>> df.where(pd.notnull(df), None) 0 0 0.5 1 None ·
Author pvieito
Medium
medium.com › @whyamit101 › pandas-nan-to-none-80a919f8fa67
pandas nan to none. The biggest lie in data science? That… | by why amit | Medium
April 12, 2025 - Can I convert None back to NaN? You absolutely can. You just need to do the reverse conversion using Pandas like this:
GitHub
github.com › pandas-dev › pandas › issues › 44485
BUG: dataframe.replace({np.nan: None}) failed when replaced even number of times · Issue #44485 · pandas-dev/pandas
November 16, 2021 - import numpy as np import pandas as pd def check_nan(df): for entry in df.to_dict(orient='records'): if any([isinstance(v, float) and np.isnan(v) for v in entry.values()]): return True return False def generate_df(): return pd.DataFrame(dict(age=[5, 6, np.NaN], born=[pd.NaT, pd.Timestamp('1939-05-27'), pd.Timestamp('1940-04-25')], name=['Alfred', 'Batman', ''], toy=[None, 'Batmobile', 'Joker'])) def where_not_working(): df = generate_df() df = df.where((pd.notnull(df)), None) print('where not working', check_nan(df)) def replace_working(): df = generate_df() df = df.replace({np.nan: None}) pri
Author wchengit
Top answer 1 of 7
276
You can use DataFrame.fillna or Series.fillna which will replace the Python object None, not the string 'None'.
import pandas as pd
import numpy as np
For dataframe:
df = df.fillna(value=np.nan)
For column or series:
df.mycol.fillna(value=np.nan, inplace=True)
2 of 7
37
Here's another option:
df.replace(to_replace=[None], value=np.nan, inplace=True)
Bobby Hadz
bobbyhadz.com › blog › replace-none-with-nan-in-pandas
How to replace None with NaN in Pandas DataFrame | bobbyhadz
April 11, 2024 - You can use the pandas.DataFrame.fillna() method to replace None with NaN in a pandas DataFrame.
Reddit
reddit.com › r/learnpython › how to fillna with none in a pandas dataframe?
r/learnpython on Reddit: How to fillna with None in a pandas dataframe?
May 2, 2018 -
Pretty straightforward, I have a dataframe that has columns with different mixtures of np.nan and None as the "null" value for that column. I want to get them all to be "None", but
df.fillna(None) df.replace(np.nan, None) df.fillna(values=None)
all don't work. Anyone run into this issue before?
Also why the bloody fucking hell does
np.nan==np.nan
evaluate to false? (Yes I know its by definition, but some bloke thought it was a good idea to write the definition that way.) Is that actually useful for anything? In this particular case, it makes me want to use None instead.
Top answer 1 of 2
1
Unlike a list, a dataframe has to have all elements be the same type. You can't insert None into a dataframe of floats, because None is not a float. However, nan is a float.
2 of 2
1
I agree with u/novel_yet_trivial , but if you really want to disregard our advice and do it anyway I believe this will work. df.where(False, None)
Note.nkmk.me
note.nkmk.me › home › python › pandas
Missing values in pandas (nan, None, pd.NA) | note.nkmk.me
August 2, 2023 - If you want to treat certain values as missing, you can use the replace() method to replace them with float('nan'), np.nan, or math.nan. pandas: Replace values in DataFrame and Series with replace()
GitHub
github.com › pandas-dev › pandas › issues › 17494
in consistent result with replace(np.nan, None, inplace=True) · Issue #17494 · pandas-dev/pandas
September 11, 2017 - >>> data = [ ... {'hello': 1, 'mad': 2, 'world': 3}, ... {'mad': 2, 'world': 3}, ... {'world': 1} ... ] >>> df = pd.DataFrame(data) >>> df hello mad world 0 1.0 2.0 3 1 NaN 2.0 3 2 NaN NaN 1 >>> df.hello.dropna() 0 1.0 Name: hello, dtype: float64 >>> import numpy as np >>> df.hello.replace(np.nan, None, inplace=True) >>> df.hello 0 1.0 1 1.0 2 1.0 Name: hello, dtype: float64 >>> Details · commit: None python: 2.7.12.final.0 python-bits: 64 OS: Linux OS-release: 4.4.0-1032-aws machine: x86_64 processor: x86_64 byteorder: little LC_ALL: None LANG: en_US.UTF-8 LOCALE: None.None · pandas: 0.20.3
Author fsck-mount
Pandas
pandas.pydata.org › pandas-docs › stable › generated › pandas.DataFrame.fillna.html
pandas.DataFrame.fillna — pandas 2.3.3 documentation
The page has been moved to this page
GitHub
github.com › pandas-dev › pandas › issues › 29024
Inconsistent behavior for df.replace() with NaN, NaT and None · Issue #29024 · pandas-dev/pandas
October 16, 2019 - Replacing NaT with None (only) also replaces NaN with None. Replacing NaN with None also replaces NaT with None
Author K3UL
Saturn Cloud
saturncloud.io › blog › how-to-replace-none-with-nan-in-pandas-dataframe
How to Replace None with NaN in Pandas DataFrame | Saturn Cloud Blog
January 16, 2024 - In this blog, if you find yourself in the role of a data scientist or software engineer, you might encounter a scenario necessitating the replacement of None values with NaN in a Pandas DataFrame. This task is routine when dealing with data, as NaN values are commonly employed in Pandas to ...
JanBask Training
janbasktraining.com › community › data-science › pandas-replace-nan-with-none
Replace None with NaN in pandas dataframe | JanBask Training Community
July 8, 2021 - I have table x: website0 http://www.google.com/1 http://www.yahoo.com2 NoneI want to replace python None with pandas NaN. I tried:x.replace(to_rep