Pandas
pandas.pydata.org › docs › reference › api › pandas.DataFrame.where.html
pandas.DataFrame.where — pandas 3.0.6 documentation
Where cond is True, keep the original value. Where False, replace with corresponding value from other. If cond is callable, it is computed on the Series/DataFrame and should return boolean Series/DataFrame or array. The callable must not change input Series/DataFrame (though pandas doesn’t ...
W3Schools
w3schools.com › python › pandas › ref_df_where.asp
Pandas DataFrame where() Method
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Pandas where() Explained with Multiple Examples - YouTube
08:21
Search-and-replace Pandas values with "where" and "mask" - YouTube
Pandas Where | pd.DataFrame.where()
05:19
How to Use where() in Numpy and Pandas (Python) - YouTube
01:34:11
Complete Python Pandas Data Science Tutorial! (2024 Updated Edition) ...
06:40
Very Useful Pandas Functions: Pandas DataFrame mask() vs where() ...
GeeksforGeeks
geeksforgeeks.org › python › python-pandas-dataframe-where
Pandas DataFrame.where()-Python - GeeksforGeeks
June 24, 2025 - import pandas as pd import numpy as np df = pd.DataFrame({'A': [1, -2, 3], 'B': [-1, 5, -6]}) res = df.where(df > 0) print(res) ... Explanation: df.where(df > 0) keeps values where the condition is True (greater than 0) and replaces others with NaN. DataFrame.where(cond, other=nan, inplace=False, axis=None, level=None, errors='raise', try_cast=False) ... Example 1: In this, we are replacing negative numbers with 0 using the other parameter...
Spark By {Examples}
sparkbyexamples.com › home › pandas › pandas.dataframe.where() examples
pandas.DataFrame.where() Examples - Spark By {Examples}
October 8, 2024 - pandas.DataFrame.where() function is similar to if-then/if else that is used to check the one or multiple conditions of an expression in DataFrame and
Pandas
pandas.pydata.org › pandas-docs › stable › reference › api › pandas.DataFrame.where.html
pandas.DataFrame.where — pandas 3.0.5 documentation
Where cond is True, keep the original value. Where False, replace with corresponding value from other. If cond is callable, it is computed on the Series/DataFrame and should return boolean Series/DataFrame or array. The callable must not change input Series/DataFrame (though pandas doesn’t ...
Statology
statology.org › home › how to use where() function in pandas (with examples)
How to Use where() Function in Pandas (With Examples)
August 10, 2021 - The following code shows how to use the where() function to replace all values that don’t meet a certain condition in an entire pandas DataFrame with a NaN value.
IONOS
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How to apply conditions in pandas DataFrames with where()
June 26, 2025 - Suppose you have a DataFrame with a company’s sales results, and you only want to display the positive results. Negative results, on the other hand, should be replaced with 0. You can do this with pandas DataFrame.where().
EDUCBA
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Pandas DataFrame.where() | Syntax,Parameters and Examples
April 3, 2023 - So the where method in pandas is responsible for searching the pandas data structure like a series or a dataframe on a given condition and replace the remaining elements which do not satisfy the condition with some value.
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Top answer 1 of 3
82
Try:
(df['A'] + df['B']).where((df['A'] < 0) | (df['B'] > 0), df['A'] / df['B'])
The difference between the numpy where and DataFrame where is that the default values are supplied by the DataFrame that the where method is being called on (docs).
I.e.
np.where(m, A, B)
is roughly equivalent to
A.where(m, B)
If you wanted a similar call signature using pandas, you could take advantage of the way method calls work in Python:
pd.DataFrame.where(cond=(df['A'] < 0) | (df['B'] > 0), self=df['A'] + df['B'], other=df['A'] / df['B'])
or without kwargs (Note: that the positional order of arguments is different from the numpy where argument order):
pd.DataFrame.where(df['A'] + df['B'], (df['A'] < 0) | (df['B'] > 0), df['A'] / df['B'])
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pandas 2.2 update: Series.case_when
From pandas 2.2.0, the API provides a pandaic alternative to np.where and np.select.
Using case_when:
cond = (df['A'] < 0) | (df['B'] > 0)
df['C'] = (df['A'] / df['B']).case_when([(cond, df['A'] + df['B'])])
# or
df['C'] = 0 # Or pd.NA or any reasonable default.
df['C'] = df['C'].case_when([(cond, df['A'] + df['B']),
(~cond, df['A'] / df['B']),
])
You notice that case_when allows you to provide an arbitrary list of conditions and replacement pairs, so this can generalize to several conditions easily (much like np.select).
Using np.where:
df['C'] = np.where((df['A'] < 0) | (df['B'] > 0), df['A'] + df['B'], df['A'] / df['B'])
Pandas
pandas.pydata.org › pandas-docs › version › 0.22 › generated › pandas.DataFrame.where.html
pandas.DataFrame.where — pandas 0.22.0 documentation
For further details and examples see the where documentation in indexing.
Medium
medium.com › @chanushkr › understanding-numpy-where-vs-pandas-dataframe-where-a-comprehensive-guide-457b5c0403c1
🧩 Understanding numpy.where vs. pandas.DataFrame.where: A Comprehensive Guide 🚀 | by Chanush KR | Medium
July 26, 2024 - Example: Imagine you have a NumPy array of sales data and you want to mark values below a certain threshold as -1. ... If the sales value is greater than 150, then keep the original value.
Vultr Docs
docs.vultr.com › python › third-party › pandas › DataFrame › where
Python Pandas DataFrame where() - Filter Data Conditionally | Vultr Docs
December 26, 2024 - In this article, you will learn how to effectively utilize the where() function in Python's Pandas library to filter and manipulate data conditionally.
w3resource
w3resource.com › pandas › dataframe › dataframe-where.php
Pandas DataFrame: where() function - w3resource
Pandas DataFrame - where() function: The where() function is used to replace values where the condition is False.
Statology
statology.org › home › pandas: how to use equivalent of np.where()
Pandas: How to Use Equivalent of np.where()
June 24, 2022 - And here’s the basic syntax using the pandas where() function: df['col'] = (value_if_false).where(condition, value_if_true) The following example shows how to use the pandas where() function in practice.
Educative
educative.io › answers › what-is-pandas-dataframewhere-in-python
What is Pandas DataFrame.where() in Python?
Line 10: We invoke the DataFrame() method from the Pandas package to convert this nested list into a DataFrame of Name, Class, and Marks.
Pandas
pandas.pydata.org › docs › reference › api › pandas.DataFrame.query.html
pandas.DataFrame.query — pandas 3.0.6 documentation
See also the Python documentation about lexical analysis in combination with the source code in pandas.core.computation.parsing. Examples · >>> df = pd.DataFrame( ... {"A": range(1, 6), "B": range(10, 0, -2), "C&C": range(10, 5, -1)} ... ) >>> df A B C&C 0 1 10 10 1 2 8 9 2 3 6 8 3 4 4 7 4 5 2 6 >>> df.query("A > B") A B C&C 4 5 2 6 ·
Swdevnotes
swdevnotes.com › python › 2020 › pandas-dataframe-where
Pandas - Dataframe Where function | Software Development Notes
November 1, 2020 - Pandas Dataframe Where method is used to replace data in the dataframe where the condition is false and is not used for filtering data like the Where clause in SQL. Filtering data based on conditions in rows and columns can be done with loc and iloc.
Medium
medium.com › @stacymacbrains › pandas-where-vs-numpy-where-df68efcb580f
Pandas where vs. NumPy where. Pandas where and NumPy where are… | by Ogochukwu Stanley Ikegbo | Medium
November 25, 2024 - Example: import numpy as np · arr = np.array([1, 2, 3, 4, 5]) result = np.where(arr > 3, 'Large', 'Small') print(result) Key Differences: Data Structures: Pandas where operates on DataFrames, while NumPy where operates on NumPy arrays. Flexibility: NumPy where is more flexible and can be used for various array operations beyond simple conditional replacement.
Real Python
realpython.com › pandas-dataframe
The pandas DataFrame: Make Working With Data Delightful – Real Python
March 18, 2026 - In this example, the condition is df['django-score'] >= 80. The values of the DataFrame or Series that calls .where() will remain the same where the condition is True and will be replaced with the value of other (in this case 0.0) where the ...
Pandas
pandas.pydata.org › docs › user_guide › 10min.html
10 minutes to pandas — pandas 3.0.6 documentation
pandas provides various facilities for easily combining together Series and DataFrame objects with various kinds of set logic for the indexes and relational algebra functionality in the case of join / merge-type operations.