bool(), a. -10 1023. provides metadata) using known indicators, important for analysis, visualization, and interactive console display. 0 John A C 1 NaN John B D 2 2. If there is a way to chain np. If this could be done in one step it would also avoid the implicit conversion from int to float that occurs below. B & C == @row. Before you read on, ensure that your directory tree looks like this: . 5 0. 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. Why in Python, using Pandas, we cannot use the following to assign a value to the first observations of each group? where the DataFrame looks like: In other words, I want. This isn't quite what I'd like though. Here's the code: In [1]: df['domainId'] = df. ord essentially gives the ordering of the entries when ( prop, chi and id) all have the same value. Jan 29, 2016 · A perhaps more intuitive method is to calculate the minima per group of letters, then use group-wise . DataFrame({'ID':['1','1','1','1','1','2 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. Of course, if you wanted it to start from one you just need to add a + 1 at the end. iterrows(): if len(df. DataFrameGroupBy. 0 John A C 3 NaN John B D 4 4. Condition2 # For a given group R1,R2,W, if TYPE (A) row amount2 is not equal to TYPE (B) row amount2 , we need sum up the amount1 Sep 10, 2017 · Let say I have this dataframe: raw_data = {'regiment': ['Nighthawks', 'Nighthawks', 'Nighthawks', 'Nighthawks', 'Dragoons', 'Dragoons', 'Dragoons', 'Dragoons Jan 30, 2017 · 2. I want to add a column of values to the existing data frame by assigning values to corresponding indexes. Some logic explanation can be seen as. groupby('col1'). isin(['bias'])]. Giving value to a dataframe column Jan 1, 2016 · df['label'] = df. The column you groupby your dataframe becomes the index of the grouped dataframe, you need a second column to do this. 4,407 9 48 80. Some rows will not have a Sequence number, so I Mar 5, 2014 · 1. One such powerful tool for handling large datasets is Pandas, a highly revered Python library. cut. This doesn't guarantee your proportions are kept. A groupby operation involves some combination of splitting the object, applying a function, and combining the results. 0, make outlier as 1, else 0. I want to create a new variable (cancer_type) that takes the values from the disease code variable (cancer_code) and assign a category (values of 1 to 12 for example) to cancer_type. Note: You can find the complete documentation for the GroupBy operation in pandas here. Note that . As @JonClements suggests, you can use pd. This echoes the answer to the question linked here: pandas create new column based on values from other columns. 5, 12. can be used) and call cumsum() on it to create a Series where each group has a unique identifying value. Returns a new object with all original columns in addition to new ones. agg(max) name value 0 A 3 1 B 2 2 A 5 3 B 3 Any clue how to do this? Mar 18, 2014 · for randomly selecting just one row per group try: df. 4, 0. 5, 36. I want the result to look like this: Feb 1, 2019 · The accepted answer (suggesting idxmin) cannot be used with the pipe pattern. print(df) Both of the above should give you the following: val label. A = s without the workaround, you are actually trying to assign pandas. 2. inf] Nov 19, 2021 · I would like to create a new column new_group with the following conditions: If there are 2 unique group values within in the same id such as group A and B from rows 1 and 2, new_group should have "two" as its value. loc and then assign a value to any row in the column (or columns) where the condition is met. Here is the code to produce the dataframe Apr 21, 2021 · One trick is replace not matched values to missing values instead filtering: print (df. This is especially useful if the sizes Mar 20, 2018 · Pandas: pd. Nov 8, 2018 · assign unique ID to each unique value in group after pandas groupby Hot Network Questions Can't set time to wee hours of January 1, 1970 Feb 21, 2024 · Mastering the manipulation of data is a cornerstone of becoming proficient in data science and analysis. Condition1 # For a given group R1,R2,W, if TYPE (A) amount2 is equal to TYPE (B) row, we need to bring the complete TYPE (A) row as output. numbers == m, 'is_min'] = 1. You can find a complete list of ranking methods you can use with the rank() function here. So I'd like to obtain something that looks like. I was wondering if there was an easy way to assign a unique numeric ID to groups in Aug 15, 2017 · So I already have one solution, which is a dead simple python loop iterating two values (One for id, one for index) and assigning the individual an id based on whether they match the previous individual: 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. - Takes in 3 parameters: Parameter 1: dataframe name Parameter 2: a column name from a dataframe Parameter 3: a number of categories, for example I want (5). index). If either of them is positive, the result will be greater than 1. Here you'd pass the cutoff values to cut, and this will categorise your values, by passing labels=False it will give them an ordinal value (zero-based) so you just +1 to them. If the values are callable, they are computed on the DataFrame and assigned to the new columns. Download Datasets: Click here to download the datasets that you’ll use to learn about pandas’ GroupBy in this tutorial. This is the fastest answer, and it works for selecting rows that span multiple columns. -15 1021. Oct 13, 2022 · groupby and assign value based on condition. Like others, Pandas 0. groupby() provides a function to split the dataframe, apply a function such as mean() and sum() to form the grouped dataset. groupby column. First, I need to groupby Tag column then if M_Name column have more than 1 different letter, the whole Tag group will have a new value "Invalid" under Tag_2 column. read_csv then the following code might be helpful for you. – toniitony. Out[1]: Aug 29, 2022 · The mean points value for players on team A and position G is 22. Sep 15, 2016 · 0. This code works, but I would like to do it not-in-place, perhaps using assign or apply. Assuming you can load your data directly into pandas with pandas. 66875. groupby('letters'). Used to determine the groups for the groupby. ie. If you want to ordinally rank values in each group, then you can transform pd. loc, and assign your desired value in c2 at those indices: Jun 21, 2017 · What is the correct way to identify max value in subgroup and assign each row value based on whether it is max or not? Here is an example df: group subgroup A 1 B 1 A 2 A 3 A 4 B 2 C 2 C 1 Apr 26, 2018 · This can usually be done by concatenating the values in each pd. Group by based on a value of a column. bins to be assigned: then first find group starters, (str. Sep 22, 2020 · I tried to assign the value to the first row of a group after groupby? Input: ID Num Aa 100 Bb 200 Cc 300 Bb 400 Aa 500. I'm trying to group them How can I do that? UPDATE1: Based on BobHaffner's comments, I've done this Oct 2, 2016 · While the other answers here give very good and elegant solutions to the asked question, I have found a resource that both answers this question in an extremely elegant fashion, as well as giving a beautifully clear and straightforward set of examples on how to accomplish join/ merge of dataframes, effectively teaching LEFT, RIGHT, INNER and OUTER joins. This is my data frame df. The new column 'C' will have a value of 0 if the values in columns 'A' and 'B' are equal, a value of 1 if the value in column 'A' is greater than the value in column 'B', and a value of -1 if the value in column 'A' is less than the value in column 'B'. Now call function in a group by statement. astype('float'), [0. For instance, if we want the sequence for patients visits sorted based on their visit date, the following code can be used. reset_index() Just be careful, the new column is called index, it should be renamed. 0). where() in such as way that I can assign Seq Token as User_First (same as First), User_Middle (if Type=User occurs in the middle), Agent_Middle (if Type=Agent occurs in the middle), Agent_Last (as explained above: if Agent is last), then it would I want to assign values based on a condition on index in Pandas DataFrame. Pandas: How to apply a value to a group of rows based on a specific row value? 3. name and apply a max function on df. cumcount does not work for me though I have installed Pandas 0. read_csv("test. condition = df. 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. 8 0. So for each element in group_col, we map the appropriate maximum value by doing (lambda x (the group name): groupby_returns_max_values [x]). id name value accept. groupby('Group_Id'). df['rank'] = df. 5])])). loc is strict when you present slicers that are not compatible (or convertible) with the index type. zip file, unzip the file to a folder called groupby-data/ in your current directory. grouper. I’ll show you how in the examples Jul 2, 2018 · CCD-TEMP. #. mean() The first range of B is (0, 0. In other words, this function maps the labels to the names of the groups. If there are only 1 unique group values within the same id such as group A from rows 3 and 4, the value for new_group should be An easy way to group that is to use the sum of those two columns. Nov 16, 2018 · Pandas' grouped objects have a groupby. Assign the default value first, and then use df. 13 gets installed with errors and I want to avoid to deal with Pandas 0. Pandas assign value of one column based on another. So my desired result is as follows: df. df. vals = dict([(i,'C'+str(i)) for i in range(len(df))]) Loop to cut the dataframe for each line and checking the previous 'Assign' column info to assign new value. . cut(qa_scores_data['Frame Name']. Enables automatic and explicit data alignment. contains() (and eq()) is used below but any method that creates a boolean Series such as lt(), ne(), isna() etc. And groupby accepts an arbitrary array as long as the length is the same as the DataFrame's length so you don't need to add a new column. Mar 10, 2017 · I have a DataFrame with columns = ['date','id','value'], where id represents different products. Grouper or list of such. Nov 13, 2021 · I need to create a new column Tag_2, which is based on Tag column and M_Name column. The following tutorials explain how to perform other common functions in pandas: How to Find the Max Value by Group in Pandas Oct 26, 2017 · id name value. It starts from 0, which is useful. date. empty, a. 5; if duration = 2, cost = average Jan 11, 2017 · A way that I believe is faster than the current accepted answer by about an order of magnitude (timing results below): def create_index_usingduplicated(df, grouping_cols=['a', 'b']): df. apply method upon it. I need to apply this logic to a large dataframe with many different groups. Sep 7, 2018 · df['Assign'] = np. Just type the name of your dataframe, call the method, and then provide the name-value pairs for each new variable, separated by commas. In this tutorial, we’ll delve into how you can group rows in a Pandas DataFrame based on specified ranges of values. qcut. 2 fgg 0. for idx, row in df. Assume that we have n products. 1. I need to select the row within pandas group by based on condition. 22. id has_highest_owner parent_cage 834951691 3TNF2 834951691 4D149 834951691 Yes 4TMM7 In my case I want to set the parent cage of all rows to 4TMM7 Jun 2, 2022 · I did a groupby and sum, which does have the result I want (shown in bold in the table below), but I don't know how to pull out the specific result and assign it to a new column in the original dataset: See full list on askpython. Parameters: **kwargsdict of {str: callable or Series} The column names are keywords. Aug 25, 2016 · Ask questions, find answers and collaborate at work with Stack Overflow for Teams. Even if they can be kept, the logic still uses "random" numbers to select each value. ,'valueidn'], where the values are assigned to the corresponding date-row if they exist, a NaN is assigned as value if they don't. Parameters: bymapping, function, label, pd. head(1) edited Mar 23, 2022 at 18:03. TimeGrouper('D')). family = np. In order to accomplish this i have a pandas frame that looks like this: Is there a way to add the numbers in the last column without having to iterate through the data frame? I was playing with the results of Grouping and auto incrementing group id in pandas but haven't made it work for my purposes. Thank you very much. 246394 > 0. I mean, look for yourself: >>> type(s. groupby(['ID'])['Num']. assign(c2 = df['c1']) # OR: df['c2'] = df['c1'] Then, find all the indices where c1 is equal to 'Value' using . Assign values in dataframe group using previous group row. sort_values(by=['group_ID', 'value']). I am looking to create a new dataframe with columns = ['date', 'valueid1' . Instead, I'd like to be able to enumerate the entries of each group g in {(id, chi)} from 0 to n_g where n_g is the size of group g. 0 1 1 24. Mar 18, 2014 · I want to build two functions. 5, 48. e. answered Oct 10, 2017 at 6:38. sort_values('B'). Oct 23, 2015 at 15:27. A & B == @row. csv") df. 92840. zeros(len(df)) # Assigning the ditionary values for output from numeric. │. 5. Or for other cells again range(1, 20), the 20th rows get their value assinged in out for 7 out of 10 rows while 3 have missing values Any idea what 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. 0 John A C 5 NaN John B D 6 NaN John B D 7 7. query: unique_combination = 1 #acts as a counter. Index-contained coordinates within a subclass instance, which somehow looks like a "counter-opposition" to the LS principle i. eval("gender=='male' and pet1==pet2 or gender=='female' and pet1==['cat','dog']") # assign values. item(), a. any() or a. 3. From trying to understand this error, do I need to set that a value >=1 is True and anything else is False before runnning this code? Jan 16, 2020 · I want to add a more extra column PrevoiousMonthQty to this Dataframe with the filled values in the Qty column by the logic that we will group by (Color, Month) and the Month is the Previous Month. groupby_sequence("name")["value"]. Oct 24, 2017 · I am trying to add quantiles based on column J1 within each ID group in the below dataframe. random. ID 0 A 1 B 2 C I want to append the Value column to it, where. The mean points value for players on team B and position F is 12. group_info[0] + 1. > 30. I did it as follows: (qa_scores_data. 0 John A C 8 NaN John B D 9 9. com Apr 22, 2019 · I have the data frame as like below one, Input DataFrame gw_mac mac 0 ac233fc015f6 dce83f3bc820 1 ac233fc015f6 ac233f264a4c 2 ac233fc015f6 I want to set the parent cage value to the value that has_highest_owner == 'Yes' Based on the grouping by the id column. shift method, which will shift a specified column in each group n periods, just like the regular dataframe's shift method: df['prev_value'] = df. groupby () Pandas df. This seems a scary operation for the dataframe to undergo, so let us first split the work into 2 sets: splitting the data and applying and combing the data. loc. I have a dataframe containing the relationship of id and its parent and some code. Additional Resources. index. 0 John A C Mar 6, 2021 · Grouping in Pandas using df. The condition is to create new columns by assigning bins to the values in columns (A-J). for i in range(1,len(df)+1,1): Jul 17, 2018 · Right now, my dataset contains two columns looking like this (first column with A, B or C, second with value): A 1 A 2 A 3 A 4 B 1 B 2 B 3 C 4 --> now I want to group by the keys of the first column (A,B,C) , and show only the keys, where the values 1 AND 2 exist. DataFrame'> Int64Index: 21210 entries, 0 to 21209 Data columns: BloombergTicker 21206 non-null values Company 21210 non-null values Country 21210 non-null values MarketCap 21210 non-null values PriceReturn 21210 non-null values SEDOL 21210 non-null values yearmonth 21210 non-null values dtypes Assign new columns to a DataFrame. It should be something like this: Jun 20, 2015 · And I want to add a column that holds the value of the group total count: Group Score Count TotalCount 0 A 5 100 155 1 A 1 50 155 2 A 3 5 155 3 B 1 40 120 4 B 2 20 120 5 B 1 60 120 The way I did this was: Apr 26, 2019 · pandas set value based on previous row only one time for each group. 6. df[ 'Age Category'] = 'Over 30'. user7864386. Once you’ve downloaded the . So duplicated is applied to gid to assert we extract the first row of each group. 3 hfd 1. This can be used to group large amounts of data and compute operations on these groups. values but only if the names are in sequence. Name: mean, dtype: float64. The axis labeling information in pandas objects serves many purposes: Identifies data (i. all(). Any helps would be very much appreciated. ihadanny. loc[black, 'color'] = 'black' Alternately, df. 13. where(df['City2']== 'C'))) Value Name City City2 0 0. i have to create a new column accept such that, if the value is greater than 1. apply(DataFrame. loc[df. core. Aug 9, 2018 · So I'd like to group by columns A and B and then assign a rank based on the value of column C function in pandas, for each group look at the value of column `C Sep 11, 2019 · If a person has a Group value that matches another ( Ax to Ay , Bx to By, e. sort_values(by=['patient', 'date']). apply to assign is_min: def set_is_min(m): df. 0. For example, if you only have one row for a specific category, it cannot guarantee your proportions are kept if your weights are all non-zero. Sep 23, 2021 · I have a pandas Dataframe and I want to create a new columns (new1,new2,new3,new4,new5,new6,new7,new8,new9,new10) from the original columns(A-J). Some of the cost values are nans, and to fill them I need to do the following: group by channel; within a channel, sum the available cost and divide by the number of * occurrences (average) reassign values for all rows within that channel: if duration = 1, cost = average * 1. 2016-01-01 12:00:00 40 1. This line of code assigns a new column 'C' to the DataFrame 'df'. Many thanks Mar 30, 2022 · How might I get the value for each Key, given that Type is equal to B and assign that result to every A? I need to apply this logic to a large dataframe with many different groups. With the new column this works just fine: Mar 5, 2021 · I want to group the rows by asset id, and then give each row an overall rank based on method_rank ascending and conf_score descending. groupby('group_ID'). csv is the filename. This looked like it worked, however, weirdly I get some random missing values. So that my new data set looks like: A 1 A 2 B 1 B 2 Oct 17, 2021 · Method 3: Using Numpy. For example, in our case, we can group the data on Nobel prizes by prize category: I want to set the parent cage value to the value that has_highest_owner == 'Yes' Based on the grouping by the id column. The target DataFrame I expected looks like this. Dec 19, 2017 · Pandas: aggregate column based on values in a different column. DataFrame({&quot;value&quot;: range(1,11)}) df # A groupby operation involves some combination of splitting the object, applying a function, and combining the results. cut to the desired numeric column. 4]). If you want the sequence to be sorted based on the values of another column, first sort the dataframe and then add the new sequence column. head, n=1) This is possible because by default groupby preserves the order of rows within each group, which is stable and Oct 8, 2018 · Assigning values in Pandas dataframe based on values from other field. However, it is often the case the number of columns that define a group, their dtype, or the value sizes make concatenation an impractical solution that needlessly uses up memory. groupby('A'). 6, 0. inf) and category names, then apply pd. – Delforge. Aug 9, 2021 · With the syntax above, we filter the dataframe using . I've tried a few things so far, the last attempt looking as follows: >>> data_set['Offset'] = data_set[data_set['img_type']. For example using integers in a DatetimeIndex. import pandas df = pandas. Pandas: changing values of a group under a condition. MultiIndex. df['sequence'] = df. This function will then work out the maximum, minimum, and return rages of values based on the fact I want 5 categories: (1,2), (3,4), (5,6), (7 Oct 23, 2015 · 7. choice. groupby('object')['value']. import pandas as pd try_df = pd. DataFrame. min(). try using pd. head: data. mins = df. Honestly, adding multiple variables to a Pandas dataframe is really easy. 8. transform ('max') will give you a date series with maximum date for each dealer. Code: base_df['Sum'] = base_df. I'd need one Series/array/list because I'm trying to assign the these values to a new column in the df above (see `col4'). Output: ID Num Sum Aa 100 600 Aa 500 Bb 200 600 Bb 400 Cc 300 300. /. Explore Teams Create a free Team Oct 14, 2021 · Say that I have a df like this:. So df. ngroup(): enumerates the group to create indices Indexing and selecting data. transform('sum') However, this code will assign the value 'Sum' to every row in the group: My output: ID Jun 30, 2021 · These codes consist of either 5 numbers or "DC" followed by 2-3 numbers (string variable). I want to divide the value of each column by 2 (except for the stream column). 1 asd 0. sort_values(grouping_cols, inplace=True) # You could do the following three lines in one, I just thought # this would be clearer as an explanation of what's going on: duplicated = df. 20–30. numbers. values = [2, 5] indexes = [1, 2] So the new data frame should look like this: ID Value 0 A 1 B 2 2 C 5 How should I do it? Thanks. where(). Now you compare this series with your date column which will return a boolean series. __name__ 'Index' whereas Mar 14, 2022 · This method assigns a value of 1 to the largest value in each group. You only need to define your boundaries (including np. import pandas as pd df = pd. Any pointers would I have a large data set in the following format: id, socialmedia 1, facebook 2, facebook 3, google 4, google 5, google 6, twitter 7, google 8, twitter 9, snapchat 10, twitter 11, facebook I want If the dataframe is already sorted on value, then you can cumulatively count the position of the values in each group. Use a. Value 0 True 1 True 2 False 3 False 4 False 5 True 6 True 7 False 8 True 9 True And say that I want to assign each group of True values a label, such that consecutive True values are assigned the same label because they constitute a cluster, whereas False values get always 0: 19 201 R 69 0. May 8, 2015 · Because when you do directly df. Function 1. groupby() function. groupby(['Video Name', pandas. groupby ('dealer'). Dec 10, 2021 · Applying duplicated to the taken value is dangerous since it will remove values in another group should the values happened to duplicate (e. Change all values in column if a condition is met within a Oct 4, 2018 · You can use GroupBy with np. # evaluate the condition. groupby('CCD-TEMP My first approach was to use a for loop and check for every row, if I find more than one combination in the dataframe of the row's values with . groupby(df. where can be used to do the assignments. shift() For the following example dataframe: print(df) object period value. cumcount(ascending=False) + 1. df['unique_combination'] = 0. The City and Domain are not considered in the comparison, but all columns need to remain. 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. Example : df. A pipe-friendly alternative is to first sort values and then use groupby with DataFrame. There are multiple files like this, but the value ranges are defined in the same XML file. C')) > 1: I have multiple CSV files with values like this in a folder: The GroupID. 5, 24. Jan 26, 2022 · Thanks. groupby("id"). Now, we want to apply a number of different PE ( price earning ratio)groups: < 20. sample(frac = 1. Existing columns that are re-assigned will be overwritten. where((df['SibSp'] + df['Parch']) >= 1 , 'Has Family', 'No Family') Oct 29, 2020 · If you want to add multiple variables, you can do this with a single call to the assign method. transform doesn't change the shape of the data frame unlike groupby which aggregates. loc[white, 'color'] = 'white' df. an instance of pandas. g. What I need to do now is apply those values to a new column called 'Offset' to a group of all rows based on CCD-TEMP. query('A == @row. id has_highest_owner parent_cage 834951691 3TNF2 834951691 4D149 834951691 Yes 4TMM7 In my case I want to set the parent cage of all rows to 4TMM7 Aug 30, 2012 · In [261]: bdata Out[261]: <class 'pandas. cumcount() df. Here you can see how the cuts were calculated: I want to assign values to a column depending on the values of an already-existing column. if l == [0. May 3, 2018 · Assign dataframe values of one set of rows to another set of rows based on a condition for specific columns 5 In Pandas with Groupby: assign a value from a column conditioned on another column Jul 15, 2015 · Pandas Set value in a group based on condition. Oct 31, 2018 · Note that I used the Seq_ID value to get the first row in the group. groupby('orgid'). apply(max_bal) col1 a [No, No] b [No, No, No, Yes] dtype: object These are the correct values but not returned in a Series as I would expect. frame. 2016-01-01 00:00:00 10 1. groupby(pd. groupby('patient Dec 21, 2019 · Pandas If row value contains items from a list as substrings, add new colum with values present on substring 0 Finding a substring (from list of strings) in a string column and add as a new column in Dataframe . For instance, I'd have a range(1, 20) in my lut_dict for one cell, but it in df1 it would only go to 19. Mar 17, 2016 · cumcount() returns integers rather than floats, which is probably what you want for an id. The mean points value for players on team B and position G is 24. apply(set_is_min) In large dataframes, this method is actually 20% faster than using transform: # timeit with 100'000 rows. print(df) To group by time more generally, you can use TimeGrouper: df['label'] = df. ID == 103, 'FirstName'] = "Matt" df. duplicated(subset=grouping Jun 29, 2021 · Pandas - Assign unique ID to each group in grouped data 1 How to get a column of group id values for a pandas DataFrame based on the groups produced by a groupby operation The lambda function does a groupby on group_col and returns the maximum values of the odds column in each group. Mar 5, 2019 · ValueError: The truth value of a Series is ambiguous. ID == 103, 'LastName'] = "Jones" As mentioned in the comments, you can also do the assignment to both columns in one shot: This is a one line of code that achieves the desired result. 4 erw 0. loc to assign specific values for each condition: df['color'] = 'colorful' df. 155, I suppose 0. Feb 2, 2022 · At this stage, we call the pandas DataFrame. I'm trying to create a dataframe where I'd have parent_id and a code based on condition if number of children_ids with the same code as parent code is at least 50% then parent code is assigned, if not it's empty. cut for this, the benefit here being that your new column becomes a Categorical. You can just create one like this: df = df. loc[1:2, ("points")] = 2. bins = [0, 2, 18, 35, 65, np. The following tutorials explain how to perform other common operations in Oct 31, 2018 · And I want to group it on df. Pandas groupby use aggregate based on two columns. date). 155) while the first row of B is 0. We use it to split the data into groups based on predefined criteria, along rows (by default, axis=0), or columns (axis=1). If it only has 1 letter in the M-Name for the same Tag group then it will be "Valid". Among these group, I had to further group them based on range of values in the second column. A similar approach is to make repeated assignments based on each condition. The indices of these returned values are the name of the group they belong to. Select to Set Values Using Multiple Conditions. assign(Value = df['Value']. ) and the Sequence number is the same, populate the Compared Group and Compared Value columns with the respective Group and Value. 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. hj kl fw jw zi jg xd ud cs xe