Replace values in column pandas based on condition

pos) CustAC = [a for a in aPos if a. isna()) | (df['column2']==0) Jan 27, 2018 · I want to replace NaN values of Age gender wise e. Sep 1, 2019 · 1. 1. So i was wondering if there is a more elegant solution. I have used the following: df. nan will not work. iloc:. Pandas’ loc can create a boolean mask, based on condition. If you want to replace multiple column values, this can also be specified inside the square brackets. loc[df[ 'column name'] condition, 'new column name Dec 20, 2023 · 1. where items is a list with different strings that I need to replace with 'other' in column 'A'. price pct date. iloc. 4. I want to select all values from the First Season column and replace those that are over 1990 by 1. where(). DataFrame. import pandas as pd df = pd. Apr 28, 2016 · How do I do it if there are more than 100 columns? I don't want to explicitly name the columns that I want to update. ix which is a mix between . loc, but all I can seem to do is replace all values of the column with one string. The following examples show how to use this syntax in practice. For example, {'a': 1, 'b': 'z'} looks for the value 1 in column ‘a’ and the value ‘z’ in column ‘b’ and replaces these values with whatever is specified in value. So assuming you mean np. This echoes the answer to the question linked here: pandas create new column based on values from other columns. The loc method allows us to select rows and columns based on labels or boolean arrays. Performance If performance is critical then you might want to know the price you pay for using . For example, df['column']. replace('Unknown', 'something') But i cant work out how to combine these to only replace unknowns for each country based on mode of occurrence of cities. This can be useful when you want to replace certain values in a column with a different value. loc to change the values in the DataFrame in place: df. Series, except_values: list = None) -> dict: """. We can use this function to replace values in a column based on some condition. For a single column criteria this can be done very elegantly with a dictionary (e. Jan 17, 2024 · Use the where() method to replace values where the condition is False, and the mask() method where it is True. If you want to stick with rename: def renaming_fun(x): if "NULL" in x or "UNNAMED" in x: return "" # or None. The method also incorporates regular expressions to make complex replacements easier. The code only replaces the value for column fare. Most Efficient way: boolean indexing with df. This is the way I want to filter my data so I don't lose the index values. In case you want to replace values in a specific column of pandas DataFrame, first, select the column you want to update values and use the replace() method to replace its value with another value. 01 times longer than the fastest. Replace values in multiple columns Pandas using df. By using a label or boolean array, the loc[] allows you to access a collection of rows and columns. index, df. Nov 30, 2020 · And the answers I've found on other stackoverflow answers have all mostly been just changing the value in a single column based on some set of conditions. Let’s implement using the above example. Another method is by using the pandas mask (depending on the use-case where) method. Replace Values in a Specific Column. Oct 2, 2015 · You do not have to use re like in the example that was marked correct above. I'm not sure if there is an issue setting a columns value that is also in the where condition off hand but you could always create a temp column and rename/drop other outputs based on that. Changing a date value in pandas based on condition and converting to datetime. See in operator, float ("NaN") and np. where(df["col_name"]=="defg", np. where(condition, new_value, DataFrame. You then want to apply the following IF conditions: If the number is equal or lower than 4, then assign the value of ‘ Yes ‘. apply(lambda row: value if condition true else value if false, use rows not columns) df. loc and . replace with regex parameter set to True and pass the mapping dictionary. For this purpose you will need to have reference column between both DataFrames or use the index. My question is, which of the above is the preferred way to replace a value based on a condition in pandas? Least Efficient way ( NOT RECOMMENDED ): looping over both columns and manually replacing each value if they meet the condition -that is if they are sah or sip. for a in ACPurchased: aPos = self. This task can be done in multiple ways, we will use pandas. You can read more about it here. where()). loc[0:15,'A'] = 16. nan type. loc[(df['First Season'] > 1990)] = 1. But if you use a pretty similar code like this. Dec 3, 2018 · Replace values in dataframe column depending on another column with condition 1 replacing a value based on value in other column, and leave as it is if condition not met I'd like the values on one column to replace all zero values of another column. halon_gas that is >20, I want to replace that entire row with NaN. Dec 2, 2022 · Method 4: Using mask () function from pandas. Than it will give back just a copy of your dataframe with changed value and doesn't change the value in the original df object. return x. price. df = df. loc property to apply a condition and change the value when the condition is true. loc[df["col_name"]=="defg Jul 10, 2023 · In this article, we will replace values in columns based on conditions in Pandas. B = df. Writing the conditions as a string expression and evaluating it using eval() is another method to evaluate the condition and assign values to the column using numpy. 193. I want to divide the value of each column by 2 (except for the stream column). replace() method is extremely powerful and lets you replace values across a single column, multiple columns, and an entire DataFrame. where to apply a conditional to a column. I am new with Pandas, so any suggestions will be most helpful. Sep 3, 2018 · However, I need to replace values in the same column given different conditions. First initialize a Series with a default value (chosen as "no") and replace some of them depending on a condition (a little like a mix between loc[] and numpy. The value parameter should not be None in this case. Also, I want to apply the same condition to another df except on columns C and D. I want to select Cabin column rows according to Pclass column's value 1. df1: Name Nonprofit Business Education X 1 1 0 Y 0 1 0 <- Y and Z have zero values for Nonprofit and Educ Z 0 0 0 Y 0 1 0 df2: Name Nonprofit Education Y 1 1 <- this df has the correct values. To replace a value with another value in dataframe column, pass the value to be replaced as the first argument and the value to be replaced with as the second argument to the replace () method. This could mean that an intermediate result is being cached. Similar results via an alternate style might be to write a function that performs the operation you want on a row, using row['fieldname'] syntax to access individual values/columns, and then perform a DataFrame. get_loc("BNP") df. Sep 21, 2023 · Replacing all values in a column, based on condition. mask(condition, A) When condition is true, the values from A will be used, otherwise B's values will be used. df = pd. I have a Pandas dataframe with a column full of values I want to replace with another, non conditionally. car = df. To learn more about the Pandas . The DataFrame. If this post helps, please consider accept as solution to help other members find it more quickly. transform(np. The data set is a bit more than a million rows by 15 columns, so it needs to be fast. You can treat this Jan 8, 2019 · def create_unique_values_for_column(column: pd. AC,b. # 1 abc. The easiest way is to use the replace method on the column. # replace Tech with "Tech & Data" using masking. where(df. mask () function can be used to change the values in a DataFrame column based on a condition. apply() and of possible approaches to mitigate it: The following is slower than the approaches timed here, but we can compute the extra column based on the contents of more than one column, and more than two values can be computed for the extra column. Solution 1: df. The loc function is used to access a group of rows and columns in a DataFrame. Jul 8, 2020 · Note that any row can be either a STR, an INT or blank. iloc[:,col1:col2] Will get me the columns I want, but trying to call loc doesn't work with multidimensional keys. You can use Pandas merge function in order to get values and columns from another DataFrame. Syntax df. Otherwise, list comprehensions will do: Apr 16, 2019 · 7. replace() is not appropriate since I don't know which values are in that column: I want to replace For anyone else arriving here from Google search on how to do a string replacement on all columns (for example, if one has multiple columns like the OP's 'range' column): Pandas has a built in replace method available on a dataframe object. Aug 30, 2021 · Step 4: Insert new column with values from another DataFrame by merge. Groupby and conditional replace. This is the general structure that you may use to create the IF condition: Copy. replace('0',df['value']. The thing is that my dataframe is very large and this approach is very slow. It replaces values with the value of other where the condition is True. . If already tried some simple "if" statement loops, but can't seem to get the syntax right. You could use DataFrame. mask(df > 100) 1000 loops, best of 3: 1. ‘No’ otherwise. Only on columns A and B: Sep 29, 2018 · 9. The replace() function in Pandas can be used to replace values with other values according to criteria. # 2 8. mask () function to change DataFrame column values condition based. dataframe. where(), and mask(), to replace values in DataFrame columns based on specified conditions. loc, and assign your desired value in c2 at those indices: Jun 19, 2023 · For example, you may want to replace all negative values in a column with zero, or replace all occurrences of a particular string with another string. loc[] property, values of the selected columns based on the provided condition of the pandas DataFrame can be replaced. This will work as a list comprehension as well, if you don't want a copy of the data returned just for a rename operation. A sample dataframe would look like this: Map me strings date 0 1 test1 2020-01-01 1 2 test2 2020-02-10 2 3 test3 2020-01-01 3 4 test2 2020-03-15 Feb 6, 2022 · 5. shift() function, this doesn't work without throwing it into a for loop. May 21, 2023 · Sure, here is an in-depth solution for pandas replace values in column based on condition in Python with proper code examples and outputs. nan == np. Dec 14, 2022 · Replace Values in a Column using DataFrame. I want to do this for 9 rows only. My attempt so far. Mar 13, 2019 · My df contains many columns. You can use rename with a lambda: df. That question brought me to this page, and the solution is DataFrame. DataFrame. assign(c2 = df['c1']) # OR: df['c2'] = df['c1'] Then, find all the indices where c1 is equal to 'Value' using . Sep 20, 2019 · Usually, I would use np. Sample story provided below is to replace the student_id with updatedId if exists in 'old_id' column and replace it with 'new_id'. e. Using . i did following code but it replace all values of cabin column with 1 even NaN values replace by 1. replace(dictionary, regex=True) # col2. However, given the . Method 1: Using loc. The returned dictionary can then be passed the pandas rename function to rename all the distinct values in a. Thanks! Jun 19, 2023 · To replace column values based on a condition, we can use the loc method of Pandas DataFrame. for row in df['Social Distancing Advisory']: if row == 'sah': row = "1". nan for more detail. loc and then assign a value to any row in the column (or columns) where the condition is met. 0 1 Joe 2018 5 7 9. The arguments are a list of the things you want to replace (here ['ABC', 'AB']) and what you want to replace them with (the string 'A' in this case): This creates a new Series of values so you need to assign this new column to the correct column name: May 1, 2014 · 3. A quick method is using . age = {25, 35, 76, 21, 23, 30} I want to do an inplace replace like this: if df. 84 ms per loop. loc[row_indexer,col_indexer] = value. Using DataFrame. ix[] supports mixed integer and label based access. It may have been necessary at one point in time, but this is not the best answer to this anymore. df. mask(mask. Below is a reproducible example of what is going wrong. replace(): for row in range(0,len(df)): df['value'] = df['value']. eval("gender=='male' and pet1==pet2 or gender=='female' and pet1==['cat','dog']") # assign values. groupby('i')['value_j']. Additionally, you can use Boolean indexing with loc or iloc to assign values based on conditions. Conditions can be formulated using logical operators such as ==, !=, <, >, etc. Jan 1, 2020 · I'm trying to replace values in a Pandas data frame, based on certain criteria on multiple columns. Apr 20, 2021 · I have a large Pandas dataframe, and want to replace some values in a subset of the columns based on a condition. replace() method, check out the official documentation here. For example, {'a': 'b', 'y': 'z'} replaces the value ‘a’ with ‘b’ and ‘y’ with ‘z’. replace(',', '-', regex=True) Source: Docs Jan 4, 2021 · Now if I print value_counts() for column 'l2' I will get count of every value in column 'l2'. loc[df['column1'] > 10, 'column1'] = 20. Note. Bear in mind that the actual dataframe that I am using has 200K records (the one I have shown above is just an example). mask = (df['column2']. COP] Oct 25, 2017 · To replace the date value based on the condition in a particular column using pandas. It is primarily label based, but will fall back to integer positional access unless the corresponding axis is of integer type. loc[df['A'] == item,'A'] = 'other'. Jan 8, 2018 · Pandas dataframe replace column value based on group. To use a dict in this way, the optional value parameter should not be given. In this example, we will replace all values in the “age” column that are greater than or equal to 50 with the value 50. I realize there are more straightforward ways to do this in general, but in my specific example I need a loop because the result for one row can depend on the prior row. breed =='AC'] for b in CustAC: AC_Data = [b. 56 ms per loop. replace() function. Copy to clipboard. Probably less efficient than the solution using replace, but an advantage is that multiple replacements could be performed in a single command while still being nicely readable, i. Jan 20, 2021 · I want to calculate a pandas dataframe, but some rows contain missing values. column. An alternative is to use the apply function. l2. How i can replace only selected rows? Dec 18, 2022 · The syntax of pandas where function is: DataFrame ['col_to_replace']. Currently, I have this. column. I did it using mask technique and also by . rename(columns=renaming_fun) It can be handy if the mapping function gets more complex. The actual syntax from pandas is: df. Here is the code, for Pandas replace multiple values in May 8, 2018 · I have a data frame with multiple columns and I wanted to replace only the maximum value of "Views" column with three different columns which are based on certain conditions. #create new column titled 'assist_more' df['assist_more'] = np. Syntax. Aug 4, 2020 · Example 3: Create a New Column Based on Comparison with Existing Column. nan, inplace=True), but it replaced all price values with NaN. The condition is for any value in the column df. This can be done using pandas' replace method, which allows you to specify the value to replace and the replacement value based on a condition. In this example we are going to use reference column ID - we will merge df1 left Nov 12, 2021 · 1. Feb 12, 2021 · I have the following dataframe, and I would like to increment 'value' for all of the rows where value is between 2 and 7. It can either just be selecting rows and columns, or it can be used to filter Jul 2, 2019 · The below code snippet would be even simpler: df. col1 = df. mask () A = B. df['flag']. loc() With the help of pandas DataFrame. In this example, only Baltimore Ravens would have the 1996 replaced by 1 (keeping the rest of the data intact). nan, I use two methods but not worked out so far: price pct date. ID Date Location Used Status AA Q121 NY 20 ok AA Q221 NY 50 ok AA Q321 NY 10 ok BB Q121 CA 1 ok BB Q221 CA 0 yes BB Q321 CA 500 yes BB Q421 CA 700 no CC Q121 AZ 50 no Oct 17, 2021 · Method1: Using Pandas loc to Create Conditional Column. rename(lambda x: x + 'NEW' if any(k in x for k in keys) else x, axis=1) ID Name Year FallScoreNEW WinterScoreNEW SpringScoreNEW. How to Perform Conditional Replacement in Pandas Apr 5, 2018 · 1000 loops, best of 3: 957 µs per loop. With that said, this is how you can transform the original code to make it work as expected. I try to replace/update price column's values based on condition of: if date is equal to 2019-09-01, then replace or update them with with np. For example if age=30 and experience=40 , replace experience with an average experience of all 30-year olds. apply method upon it. My search so far returns methods that work for a single column. Dec 23, 2017 · i have train dataset which has 12 columns. Let’s try this out by assigning the string ‘Under 30’ to anyone with an age less than 30, and ‘Over 30’ to anyone 30 or older. Solution 3: Use DataFrame. For a DataFrame a dict can specify that different values should be replaced in different columns. Aug 17, 2018 · EDITED : I want to replace a value in a cell if values on other cells satisfy the condition. date == '2019-09-01', np. columns, fill_value=False), 999) Out: a b c spam 999 999 6 ham 1 999 7 Use DataFrame. reindex(df. Sep 24, 2018 · And I can replace values with: df['column']=df. And then replace value of selected rows of Cabin column with 1. I would like to replace the nan values of the GDP column with the mode of other GDP values for the same country and region. apply(lambda x: np. The final method is to use the masking function from pandas which are generally used for replacing the values of any row/column based on certain conditions. shift(1)) I have a dataframe where I want to replace values in a column, but the dict describing the replacement is based on values in another column. For those missing values, i want to use a diffent algorithm. mean) # this gives the correct values for w in the rows where value_j is null, # except when all the adjacent nodes have null value_j (in which case it's still null) filled_means = means. df["col_name"] = np. Dec 17, 2020 · SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame When I use the following: df. So to be clear, my goal is: Dividing all values by 2 of all rows that have stream 2, but not changing the stream column. Specifically, I want to replace the values that are greater than one with 1 in every column to the right of the 9th column. An alternative is to use pandas . You can treat this Mar 2, 2023 · The . You can use numpy where to set values based on boolean conditions: import numpy as np. replace(1, 100) will replace all the occurrences of 1 in You can reindex the mask to have the same shape as df, and then use df. Jul 20, 2015 · 1003. If you want to replace value on condition false, you could consider using DataFrame Replace value in pandas dataframe based on where condition -1 How to merge every two columns, with pandas, substituting only if the left column value is nan or 0 May 4, 2016 · I have a dataframe that looks something like this: I want to replace all 1's in the range A:D with the name of the column, so that the final result should resemble: How can I do that? You can re Oct 22, 2015 · suppose I've a pandas dataframe with column values as age like this df. where(df <= 100) The slowest run took 8. Remap values in pandas column with a dict ): import pandas as pd. value_counts() Output is : My question is, how to replace all those values in this 'l2' column which have value count <3 with value 'other' My expected dataframe is : Mar 28, 2022 · I have two dataframes where I need to update the first one based on the value of the second one if exists. Documentation here. where() function. Dec 17, 2018 · 1. nan, df["col_name"]) Obviously replace col_name with whatever your actual column name is. Otherwise, if the number is greater than 4, then assign the value of ‘ No ‘. I've tried what's suggested here, but it doesn't quite determines a condition for the value of a column to be updated. Replace value in a pandas data frame column based on a condition. loc[] property can be used to replace values in a column based on a condition. # evaluate the condition. for item in items: df. **1. Mar 27, 2024 · To replace NaN values, use DataFrame. columns. Mar 10, 2015 · Pandas replace the value of a column in dataframe only where if condition is true. get_loc("MCI") col2 = df. For the purpose of this question, let's assume I don't know how long this column is and I don't want to iterate over its values. missing values for 'male' should get replaced by average age of Male and vice-versea. Simple example using just the "Set" column: 2. In [107]: %timeit df. Contents. column_name) In the following program, we will use numpy. Lets say: If column B contains a value, then substract A from B; If column B does not contain a value, then subtract A from C Oct 3, 2022 · Hi @Bebo, You can create a calculated column with SUBSTITUTE function to repalce values based on other column values: Table[Type] = "gamecode", SUBSTITUTE ( Table[Type], "code", Table[Type ID] ) Regards, Xiaoxin Sheng. # 0 5. fillna(1) # this corrects the last problem df['w'] = df['value_j']. the accepted answer shows "how to update column line_race to 0. Very interesting observation, that code below does change the value in the original dataframe. condition = df. But, it replaces all the values in that row by 1, not just Oct 26, 2021 · You can use the following basic syntax to replace values in a column of a pandas DataFrame based on a condition: #replace values in 'column1' that are greater than 10 with 20. 2. mask:. The syntax is as follows: df. mask(boolean_result, other='blue', inplace=True) inplace=True means to perform the operation in place on the data. replace('RED BULL RACING HONDA', 'HONDA') I receive no warnings/errors. DataFrame({'col1': {0:1, 1:1, 2:2}, 'col2': {0:10, 1:20, 2:20}}) 22. age >=25 and df. Mar 10, 2016 · But this trick only works if values in the two columns correlate exactly (or if values in col1 are unique). Dec 17, 2019 · In other words, I need to loop through a column and if a value contains a given string, replace the whole value with a new string. Jan 29, 2019 · The reason the comparison statements weren't working is because np. The df. 1000 loops, best of 3: 1. May 6, 2024 · Pandas offers several methods, including loc[], np. Thanks! First, you could create a new column c2, and set it to equivalent as c1, using one of the following two lines (they essentially do the same thing): df = df. loc[row_labels, column_labels] Jan 26, 2014 · 10. To work with pandas, we need to import pandas package first, below is the syntax: import pandas as pd. where (condition, new_value) condition: conditional expression col_to_replace: Name of the column in which values need to be replaced new_value: Old value will be replaced with this value if condition is False. loc[0:15]['A'] = 16. column=[valuse if condition is true else value if false for elements a,b in list from zip function of columns a and b] Dicts can be used to specify different replacement values for different existing values. The following code shows how to create a new column called ‘assist_more’ where the value is: ‘Yes’ if assists > rebounds. so, the output dataframe would look this this: Feature1 Age. get_cell_list_contents(a. isna(): Dec 19, 2020 · I am trying to perform a following task: If experience > age, replace the value of experience with an average experience of people of the same age. Sep 21, 2018 · means = df. loc[]** The DataFrame. column=df. # replace values in the 'age' column The replace () method is famously used to replace values in a Pandas. The values of a pandas DataFrame can be Aug 5, 2020 · I have a Pandas DataFrame called df (378000, 82) and I would like to replace the entire row with NaN based on a specific condition. fillna(filled_means) # this copies value_j Mar 30, 2015 · However, sometimes you want to fill/replace/overwrite some of the non-missing (non-NaN) values of DataFrame A with values from DataFrame B. 3. nan if x['A']==0 else x['B'],axis=1) zip and list syntax; dataframe. a = row['A'] b = row['B'] c = row['C'] if not c. replace is less known. DataFrame({&quot;value&quot;: range(1,11)}) df # Jul 13, 2022 · I have a dataset where I would like to map values based on a specific condition and override the values that are in an existing column. I want to replace all values only in columns A and B with NaN according to a condition. Something like the code below. where () method and replace those values in the column ‘a’ that satisfy the condition that the value is less than zero. nans, one good way to achieve your desired output would be: Create a boolean mask to select rows with np. grid. For replacing both True and False, use NumPy's np. I am trying to loop through a pandas data frame and replace values in certain columns if they meet certain conditions. replace() function in Pandas is straightforward and flexible, allowing us to replace a single value, or multiple values, or perform replacements based on conditions by passing a dictionary or a list in Python. I have always used method given in Selected answer, today I faced a need where I need to Update column A, conditionally with derived values. fillna() function to replace NaN with empty/bank. In the case of the NaN value of the GDP column of index 6, I wish to replace it with 100 (as it is the mode for GDP values for Region 1 & Country a) The desired output should look like this: Region 5 days ago · Pandas: Replace Values in Column Based on Condition. g. Appliance,b. df[ 'Age Category'] = 'Over 30'. nan or 0 value and then copy when mask is True. You can use the following basic syntax to replace values in a column of a pandas DataFrame based on a condition: #replace values in 'column1' that are greater than 10 with 20. car. mask(cond, other=nan) does exactly things you want. import pandas as PD . loc method but it did not work for me. replacing to Jun 6, 2019 · How to replace dates in a column in a pandas dataframe? 2. DataFrame['column_name'] = numpy. While my code is running fine but getting an exception as following: "SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: http May 9, 2022 · Every time there is a value of -9999999 in column Feature1 I need to replace it with the correspondent value from column Age. I've also tried some . where: Nov 22, 2020 · df: Region Country GDP. This usage of df. model. where(df['assists']>df['rebounds'], 'yes', 'no') #view Nov 26, 2015 · This post consists of two questions, touching on issues I have encountered when trying to replace elements in a Panda dataframe based on a given condition. age <= 35: replace that value with 1 else: replace that value with 0 Mar 13, 2015 · I'd like to replace the '' values in b1 and b2 with the corresponding values in a1 and a2, where b1 is blank: # a1 a2 b1 b2 # 0 m q m q # 1 n r n r # 2 o s a b # 3 p t p t Here's my thought process (I'm relatively new to pandas, so I'm probably speaking with a heavy R accent here): Feb 20, 2021 · I want to replace the values in the column 'Risk Rating' if and only if three conditions are met from three different columns of the dataframe. Below is an example where you have to derive value to be updated with: Using this you can UPDATE dynamic values ONLY on Rows Matching a mutate(var = case_when(var == 'Candy' ~ 'Candy', TRUE ~ 'Non-Candy')) The syntax for case_when is condition ~ value to replace. This simplifies processing since you can access the actual 'primitive' values in the row using the column names and have visibility of other cells in the given row/column. Data. where, use the following syntax. I want to replace the 'Risk Rating' value from 0 to 9 for this singular case. In [106]: %timeit df. You can check for the identity of the NaN element but not equality. Check value will remain same if it matches. Jun 9, 2016 · 8. Thus only replace value in col2 if col1 matches a certain condition, else leave the original value. elif row == "sip": row = "0". Creates a dictionary where the key is the existing column item and the value is the new item to replace it. For a DataFrame a dict can specify that different values should be replaced in Mar 22, 2022 · Empty cells in pandas have np. To replace a values in a column based on a condition, using numpy. loc[condition, 'column_name'] = new_value. loc[df['fare']>512, 'fare'] = 263. How to replace timestamp across the columns using pandas. Aug 9, 2021 · With the syntax above, we filter the dataframe using . Replace a particular value based on condition using groupby in pandas. xj hk wz qu aq lr bt bf fl lf