Pandas groupby delete rows

Pandas groupby delete rows. We can also choose to include NA in group keys or not by setting dropna parameter, the default setting is True. I tried it done by: df = df. This is what I want to get: Person Bank 0 1 B1 1 1 B2 5 3 B1 6 3 B1 7 3 B5 If B1 never happens, then clear all the rows that belong to that person. This would filter out all the rows with max value in the group. # pandas_airqual. Yet I do not know how to only delete rows of zero at the beginning of an account-product series. Drop last n rows within pandas dataframe groupby. agg(lambda x:x[1:]) ,but it doesn't work. One way to achieve this is to filter on the sum of EM_results values in each group, assuming these values are only ever 0 or 1: ID EM_results pa_id_1850. For example, before the transformation I would get 4 rows and after the transformation I still get 4 rows but with a new column. Mar 23, 2020 · Here's a long way to solve this, to illustrate how groupby works. reset_index(drop=True) Nov 16, 2017 · From pandas 1. (x['B'] != 't'). The drop() function is used, where the argument is the index label or a list of index labels. import pandas as pd. 3 2 c. A Cat-Tiger B Ball-Bat I tried, Jan 14, 2020 · Group Col2 Col3 Grp1 1 Grp1 1 Grp1 1 Grp1 2 Grp1 3 Grp1 3 Grp2 1 Grp2 1 Grp2 1 Grp3 1 Grp3 2 Grp3 3 Grp4 1 And I would like to groupby groups and remove all groups from the data frame where the nu Feb 20, 2019 · You could groupby iD and and use boolean indexing with idxmax to keep from where the first B is found onwards: Pandas - delete row based on first column value. It is these keys I am assigning to k. Where this equals df['count'] (by index Jan 23, 2017 · Currently, I've been removing complete series with a filter, e. value_counts. groupby (key) obj. groupby(['col'])['val']. value_counts(). : Pandas provide a unique method to retrieve rows from a Data frame. Combining the results into a data structure. Share Jun 27, 2016 · Stack Overflow Public questions & answers; Stack Overflow for Teams Where developers & technologists share private knowledge with coworkers; Talent Build your employer brand Pandas Groupby Filter to Remove Outliers From Within Each Group. Should return True or False. g. 0 2 5. Conditionally selecting values from pandas dataframe. nth(0) will return the first row of group no matter what are the values in this row, while . NOT have the last row of a group "steal" a value from a group that happens to be adjacent in Jan 30, 2018 · if count == 1: headers = line. Mar 7, 2019 · When I do a group by on these 3 columns, the nan row somehow gets deleted/dropped. Example 1: For grouping rows in Pandas, we will start with creating a pandas dataframe first. 0 1. value_counts() res = df[~df['city']. agg() method. groupby('pidx'). grouped. 3. nth. Grouping data with one key: Jul 11, 2018 · You can first calculate a series of maximums by group. Pandas drop last duplicate record and keep remaining. Jan 10, 2021 · In pandas dataframe first I want to group the data with ' batch_id ' column then check in the ' result ' column if all values are negative delete that group. That means because UNIT "a100" has the sequence [001, 002, 003, 001], it should be dropped, but the UNIT "b222" remains, because the sequence is right regardless of Jun 3, 2019 · Python pandas - select rows based on groupby. groupby('Col1'). Feb 8, 2019 · The number of rows is in the attribute . result: A. Replace all values in DataFrame May 13, 2018 · 0. sum() a c b 1. The groupby object essentially just holds metadata about how to perform the groupby so what you are trying won't work. 2. transform('count') This does create a new column, however, it's giving me all the rows. get_group('B'). So I would only like to keep the rows where grp1 is the same as grp2 for each code1 but only where dist_km is the smallest value for that specific code1. I tried below code, but it return me the last row of each group, instead I want to sort by col3 and keep the group with max col3. Aug 27, 2015 · pandas - groupby, count values and remove equal occurrences. Write a Pandas program to split a given dataset using group by on multiple columns and drop last n rows of from each group. 0. Now, let’s say we want to delete group ‘ B ‘ from our dataset. Note this will also remove duplicates maximums. split()) count += 1. Ask Question Asked 8 years, 9 months ago. loc[] method is used to retrieve rows from Pandas DataFrame. df = pd. 4 3 c. counts = df['city']. all for test if groups has no 0 values: EDIT: For remove all groups with missing values: For test missing values: Note: in pandas version 0. c = defaultdict(int) for i, x in zip(s. Then, from a each I'd like to remove records whose value for column_condition == 'B' until I reach to a row whose column_condition == 'A'. 6,273 2 23 16. Returns: DataFrame. Use the DataFrameGroupBy. head: data. 0 and above, ix is deprecated and the use of iloc is encouraged instead. set_index ("tstamp") Mar 12, 2021 · Pandas’ groupby() allows us to split data into separate groups to perform computations for better analysis. In the data you provided, a value of 20 for pidx only occurred twice so it was filtered out. duplicated(keep='first')] While all the other methods work, . astype('bool')] Jul 5, 2015 · You could use groupby/transform to prepare a boolean mask which is True for the rows you want and False for the rows you don't want. dtype: int64. read_csv("Inputfile. groupby(pd. The method works by using split, transform, and apply operations. Row Selection. groupby(['col2','col3']). append(line. Jul 7, 2021 · For each group with the column named grp, I want to drop the rows where col1 is NaN. 3,774 35 33 36. agg({'b':list}). index % 3 != 0] # Excludes every 3rd row starting from 0. groupby(['date', 'cid']). In your case repeated_names will only return ['Lucas'], but this is generalizable. You can group data by multiple columns by passing in a list of columns. In the below dataframe wherever combination for F and G occurs for an ID, I would like to remove row with value G. – EdChum. Lets say for dV = 1 and dt = 1, the wanted output would be: t V. Remove rows based on a Pandas groupby() result. Sep 29, 2023 · Dealing with Rows: In order to deal with rows, we can perform basic operations on rows like selecting, deleting, adding and renaming. df = data. For instance, say I have a dataFrame with these columns . market company price volume. Once you have such a boolean mask, you can select the sub-DataFrame using df. bymapping, function, label, or list of labels. 7 6 B inf 4 B 0. loc[:, (df >< 0). values[::-1]): Jan 24, 2017 · This is a straightforward application of filter after doing a groupby. transform with GroupBy. Parameters. groupby() method to group the DataFrame. groupby('id'). col val A Cat A Tiger B Ball B Bat import pandas as pd df = pd. And I want to delete the first line of each group based on id ,the result should like this: id values. g = df. # convert Date to datetime df ['Date'] = pd. For the example above, only these rows will Jan 14, 2019 · Let’s see how to group rows in Pandas Dataframe with help of multiple examples. Mar 31, 2017 · you can just use : df. Jun 5, 2014 · loc4 1. groupby('months_to_maturity', as_index=False) which will allow you to remove the first 2 rows on your next line. Here is a dataframe: df = pd. Maximum value from rows in column B in group 1: 5. filter(lambda x: (x['B'] != 't'). Similar to this post: enter link description here however I need to keep all By “group by” we are referring to a process involving one or more of the following steps: Splitting the data into groups based on some criteria. funcfunction. DataFrame. transform('max') df = df[~(df['count'] == g)] The series g represents maximums for each row by group. groupby () method groups a DataFrame using one or more columns. C. dataframe. Criterion to apply to each group. groupby(level = acc_prod). sort_values ( ['Person', 'Date']). We can do this by using the drop method and passing the index of the rows in the ‘ B ‘ group. code1 code2 grp1 grp2 dist_km. groupby(['country'])['count']. The last row should show NaN. You can easily apply multiple aggregations by applying the . any(axis=0)] but then it doesn't delete the whole group. I would like to group it based on "UNIT" and drop the rows that do not have the [001, 002, 003] "MACHINE" sequence. col1 col2 col3. 3 4 A 0. 65 2012-09-10 3001 5003 2 70002 Nov 19, 2012 · In [11]: g = data. filter(lambda x: len(x) > 26) And I've seen examples of removing only the first row; Python: Pandas - Delete the first row by group . How can I do this in the most efficient way? I have tried just grouping the data by ID, but since the companies can raise the same type of investment rounds in different years, this approach leads me to a wrong result. It determines the number of rows by determining the size of each group (similar to how to get the size of a dataframe, e. Drop groups that do not pass the filter. groupby() method allows you to aggregate, transform, and filter DataFrames. You can find all of the unique names that are repeated for the same date, and store them in a list. You can use groupby. Jul 6, 2018 · 5. 2. DataFrame Farmers is filled with the working progress of several farmers who send information in a certain time intervall (minutes). 0 1 10 10 20. 1 1 20 10 20. unstack(). Python3. drop(grouped. The DataFrame. Identifying statistical outliers with pandas: groupby and reduce rows into different dataframe. Given a DataFrame that looks like this: Age Died 0 26 0 1 26 0 2 27 1 3 28 0 4 28 1 5 28 1 I want to return a DataFrame that looks like this: Jan 5, 2020 · 1. Or you could write the filter the following way: Create a booleen series based on whether an row of column B Mar 23, 2019 · Its a csv dump. 1 2. Hot Network Questions I would suggest using the duplicated method on the Pandas Index itself:. Apr 30, 2023 · We can use the groupby method to group the data by the ‘ Group ‘ column: grouped = df. core. Or you can use GroupBy. I would expect the output DataFrame to look like this. Each subframe is endowed the attribute ‘name’ in case you need to know which group you are working on. python. drop(i) where i is the index or the row number. groupby(['pid', 'sid']) for above dataframe, In the 19th row uid=1, pid=1,sid=4 and in 20th row uid=1, pid=1,sid=5. How do I get rid of this? This makes it difficult to process this dataframe in subsequent processing 2. Then subset the dataframe by any rows matching these names. True by default; if False, groups that evaluate False are filled with NaNs. to_datetime (df ['Date']) # sort by Person and Date to make index usable for next step df = df. df3 = df3[~df3. In this situation 20th row pid=1 is the first occurrence for sid=5 and 24th row pid=1 is the 2nd occurrence for sid=5 . Your attempt is close: filter needs to return a scalar, not a Series. The output i expect is following: I've figured out how to find required pairs of (store_id, item_id) using pd. But I get a multi-index dataframe after groupby which I am unable to (1) flatten (2) select only relevant columns. . group = group. Feb 1, 2019 · The accepted answer (suggesting idxmin) cannot be used with the pipe pattern. Dropping Rows with Specific Conditions: You can drop rows based on certain conditions applied to the columns of the DataFrame. groupby(['price', 'company']). Wherever the values in xdiff and ydiff is less than 10 then remove the second line. loc() on dataframe to filter the rows with max Oct 11, 2022 · I'm trying to use groupby and agg() function for this data processing step: Input: ID Fruit 1 Apples 1 Oranges 2 Strawberries 3 Blueberries 4 Blueberries 4 Apples May 30, 2014 · So, for example, you could do the following: >>> df. The basic syntax of the drop () function is: Apr 8, 2017 · I am trying to get value_counts on a GroupBy object: unstacked = data. From this I want to group by imagename and brandname. Jun 5, 2017 · I tried to use groupby to group rows with multiple values. First get all Group values for Entry == 0 and then filter out them by check column Group with inverted mask by ~: Group Dist. 1, this will be my recommended method for counting the number of rows in groups (i. groupby. sum() <= 1 to only select groups where 1 appears 1 Jul 30, 2015 · Jul 29, 2015 at 13:45. Test Data: ord_no purch_amt ord_date customer_id salesman_id 0 70001 150. David Buck. If there's rows before the first appearance of B1, I want to drop them. 3 1 40 10 20. filter(lambda x: len(x) > 1) # pandas 0. Remove groups if column contain more than x number of value in a list. reset_index (drop=True) # filter for Dec 30, 2019 · The only thing I can think of to accomplish this task would be to use openpyxl. edited May 24, 2020 at 21:05. In [367]: df Out[367]: sp mt val count 0 MM1 S1 a 3 1 MM1 S1 n 2 2 MM1 S3 cb 5 3 MM2 S3 mk 8 4 MM2 S4 bg 10 5 MM2 S4 dgb 1 6 MM4 S2 rd 2 7 MM4 S2 cb 2 8 MM4 S2 uyi 7 # Apply idxmax() and use . columns. But if it goes from won to something else then I want it in the data. Futhermore, I can find the duplicate rows doing the following: Jul 14, 2016 · I want to remove the nth row of a groupby object, say the last row. Python pandas - select rows based on groupby. e. actually 24th row only want to delete, but 20th row is deleted. Here is my code: Apr 12, 2024 · To get the first row of each group in a Pandas DataFrame: Use the DataFrame. rename (columns = {"CO(GT)": "co", "Date_Time": "tstamp", "T": "temp_c", "RH": "rel_hum", "AH": "abs_hum",}). Thanks for linking this. . shape[0]: df. Applying a function to each group independently. drop([a,b,c]) where a,b,c are the list of indexes or row numbers. sort_values('B'). 5. shape[0] >= min_size) NB: If you want to remove the groups below the minimum size, keep those that are above or at the minimum size (>=, not >). filter(lambda g: (g. get_group(group_name). df. In order to reset the index after groupby () we will use the reset_index () function. value_counts returns a Pandas series object but it is like a dict. isin(counts[counts < 5]. The first 2 steps may not be necessary depending on how your dataframe is structured. To count the number of non-nan rows in a group for a specific column , check out the accepted answer . The constraint is that I do not want to drop these rows when there's multiple rows within the group. Nov 19, 2013 · To get the first N rows of each group, another way is via groupby(). I don't need all the rows. Nov 9, 2022 · In my dataframe below I wish to remove rows based on two conditions: has an id that appears two times; belong to group B; In the dataframe (data) below it would be row with index 1 and 6 that should be removed. Based on a common value, the 'ID', Where there are duplicate rows the values from another column 'HostAffected' should be combined with a line break. I could do this quickly in R using dplyr group by, lag and lead Dec 5, 2017 · I was just googling for some syntax and realised my own notebook was referenced for the solution lol. DataFrame() Jul 19, 2018 · I'm having a dataframe and I'd like to do a groupby() based a column and then sort the values within each group based on a date column. NOTE: using Pandas inplace argument where it is available is NO guarantee that a new DataFrame won't be created in memory. example = {'Team':['Arsenal', 'Manchester United', 'Arsenal', May 3, 2019 · I am looking to remove duplicates "within" a group. Oct 9, 2014 · 50. B. 2 2 k. sum(), but stuck with dropping them from Oct 20, 2015 · I find that there are some duplicate rows, so I want to see which rows appear more than once: data_groups = df. A CatTiger B BallBat I want to introduce a delimiter, so that my output looks like. Begin by creating a function which tests for the string you want: def contains_str(x, string = '_Lh'): if string in x: return True. Feb 14, 2022 · 2. Trying way too hard to guess what you want. I'd suggest to use . Jun 22, 2023 · Basic Drop Method: This method allows you to drop a single or multiple rows in a DataFrame using the row index label. Jan 25, 2019 · 4. Below are various examples which depict how to reset index after groupby () in pandas: Example 1. Below is a subset of a pandas dataframe I have and I am trying to remove multiple rows based on some conditions. df4 = df. size() It returns a pandas series with the count of rows for each group. Cool. Dec 17, 2021 · Now I want to delete all the rows where the change in V from one row to another is less than dV, AND the change in t is below dt, but still keep datapoints such that there is data at roughly every interval dV or dt. nth[:N]. name != group_name). csv", parse_dates = [["Date", "Time"]], na_values = [-200], usecols = ["Date", "Time", "CO(GT)", "T", "RH", "AH"]). groupby('tag') In [12]: g. transform with idxmax. Taking the last of each group will remove duplicats. For example, Assume the table below is one of the groups Dec 15, 2014 · So I want to drop row with index 0 and keep rows with indexes 1 and 2. Notes. index % 3 == 0] # Selects every 3rd raw starting from 0. import Aug 30, 2021 · I need to remove all tokens where the number of rows in the group are less than 3. 0. Remove group of empty or nan in pandas groupby. first() if you need to get the first row. I have a dataframe like this : id values. all()) pandas. Dataframe:- token active 0 58 1 1 58 8 2 63 5 3 63 9 4 63 0 5 97 6 6 97 1 I filtered groups having less t Unlike the previous methods mentioned, it selects a row from each group randomly (whereas the others only keep the first row from each group). For example, for the top-2 rows for each id, call: Aug 16, 2019 · That is, I want to keep the rows where Bank == B1 and the following ones. Dec 28, 2020 · I am trying to do some aggregation of fields and I get an additional row on the aggregate column- in this case 'sum'. Ideally, I would want to have the combination ( A, B and nan in this case) to be retained. Jun 25, 2021 · A simple method I use to get the nth data or drop the nth row is the following: df1 = df[df. all() allows us to only keep a group if there are no rows with a 't' in column B. So the output should be this (day doesn't matter for me here): article views 0 729910 445 (162 + 283) 1 730855 1 2 731449 2 The closest I got is: Apr 23, 2020 · I want to group rows by 'Age', and return a count of 1) how many rows make up each group, and 2) how many of those rows meet a condition. In fact, it may very well create a new DataFrame in memory and replace the old one behind the scenes. index. My goal is to keep only U rows with only one occurrence, Jun 23, 2013 · Pandas groupby and remove row if group have number > than threshold. 20. import numpy as np. Filter grouped pandas dataframe, keep all rows with minimum value in column. dropnabool. There are multiple ways to split data like: obj. Group DataFrame using a mapper or by a Series of columns. The default behavior of pandas groupby is to turn the group by columns into index and remove them from the list of columns of the dataframe. Grouper(freq="7D"))['domain']. 1. Related. groupby('A'). First save the output to excel with the multi-index using pandas then delete the column using openpyxl to maintain the format you are looking for. sum() Jan 19, 2021 · 2. fillna(0) Thus I get a nice DataFrame with domain values as columns and periods of time as rows and number of visits to a domain during a period in a corresponding cell. Dec 20, 2021 · The Pandas . apply(list) or use it with agg as part of a dict df. A pipe-friendly alternative is to first sort values and then use groupby with DataFrame. Aug 18, 2016 · I could delete specific columns based on the condition df. For example, from the first two lines I want to delete the second line, similarly from lines 3 and 4 I want to delete line 4. # create a new dataframe where the names 'Lucas' and 'Marie' are repeated for the same date. This can be used to group large amounts of data and compute operations on these groups. I am looking for a solution for deleting the last row of each group after using GroupBy. filter(lambda x: len(x) > 2) LeafID count pidx pidy. Out of these, the split step is the most straightforward. The drop () function in Pandas is used to remove specified rows or columns from a DataFrame. groupby (key, axis=1) obj. In this article, you’ll learn the “group by” process (split-apply-combine) and how to use Pandas’s groupby() function to group data and perform operations. all()) A B. Apr 9, 2018 · This is one way using pd. >>> l = [[1, 2, 3], [1, None, 4], [2, 1, 3], [1, 2, 2]] >>> df = pd. For Example: Here I want to drop 1st group because 2 < 5, so I want to keep the group with col3 as 5. Using follwoing code. 0 1. We filter the counts series by the Boolean counts < 5 series (that's what the square brackets achieve). name crit1 crit2 A 0. DataFrame(l, columns=["a", "b", "c"]) >>> df. What do you mean by first 2 rows? You could do df = df. index May 4, 2020 · I want to delete all reiterations (records/rows) when a certain A goes to won but ONLY if it stays at won (A=101). 13. first() will eventually return the first not NaN value in each column. sample(n=1) You can verify that df1 , df2 (ayhan's output) and df3 all produce the very same output and df4 produces an output where size and nunique of cid match for Jul 8, 2019 · 1. py import pandas as pd df = pd. So the df. groupby ( [key1, key2]) Note : In this we refer to the grouping objects as the keys. groupby(df. I have a Pandas dataframe, and I want to create a new column whose values are that of another column, shifted down by one row. len (df)) hence is not affected by NaN values in the dataset. However it gets dropped. counts < 5 returns a Boolean series. ix[1:-1] should be replaced by df. transform(lambda x: x. Then filter out instances where count is equal to that series. groupby('batch_id'). Sep 14, 2018 · I want to take a pandas dataframe, do a count of unique elements by a column and retain 2 of the columns. generic. Additionally, I think you could use lambda x: (x['EM_results'] == 1). Happy001. This arithmetic based sampling has the ability to enable even more complex row-selections. groupby()[]. pandas select rows after groupby. Aug 19, 2022 · Pandas Grouping and Aggregating: Split-Apply-Combine Exercise-32 with Solution. 102 12/2019 looking 102 01/2020 won 102 02/2020 archived 102 03/2020 deleted 101 12/2019 looking 101 01/2020 won. answered Jun 5, 2014 at 0:34. The outcome of this call is the same as groupby(). The Index of this dF is FarmerName. The catch is that I want to do this by group, with the last row of each group showing NaN. I can extract this row using groupby. The expected result is this one (the group of rows 222-CCC is deleted): result = A B C 111-ABC 123 EEE 111-ABC 222 EEE 111-ABC 444 XXX 333-DDD 123 TTT 333-DDD 123 BTB 333-DDD 444 AAA Dec 14, 2023 · The primary method to drop rows in Python Pandas DataFrames is the drop () function. Dec 29, 2021 · The abstract definition of grouping is to provide a mapping of labels to group names. Jun 4, 2013 · But currently, here is what I believe to be the most succinct way to filter the GroupBy object grouped by name and return a DataFrame of the remaining groups. The difference between them is how they handle NaNs, so . tolist()) size = data_groups. Oct 15, 2018 · I want to have a single row per value in article, and to have a views/total_views column that sums views number for each occurrence of the article in the row. groupby(by=["b"]). A groupby operation involves some combination of splitting the object, applying a function, and combining the results. read_csv ("groupby-data/airqual. head(N) . Groupby and remove upper outliers in Python. result != 'negative'). groupby('Group') We have grouped our data. Due big size of input file, i need to take only unique pairs - userID-locationID (some kind of preprocessing). Next, iterate over your groups and apply this function: keep_dict = {} Apr 22, 2021 · My expected output. iloc[1:-1] . \ sort_values(ascending=False). index) And here is a more general method derived from the links above: df[grouped[0]. col1|col2|col3|col4 if I apply a groupby say with columns col2 and col3 this way. 50 2012-10-05 3002 5002 1 70009 270. Series object. sum() I got. DataFrameGroupBy object at 0x0000023032788B88> – Dec 11, 2020 · It is used to split the data into groups based on some criteria like mean, median, value_counts, etc. Groupby and drop NaN rows while preserving one in Pandas. 0 2 3 2. We then take the index of the resultant Jan 5, 2021 · I actually couldn't manage to get the grouped DataFrame to print, I had to use the "For key, item in grouped" loop above to get any output. 1 Out[12]: pid tag 1 1 45 2 1 62 4 2 45 7 3 62 The function (the first argument of filter) is applied to each group (subframe), and the results include elements of the original DataFrame belonging to groups which evaluated to True. split() else: data. 4 3 Dec 23, 2016 · I want to delete all groups of rows (grouped by A) that do not contain 123 in the column B. Feb 1, 2022 · wondering how I can compare the amount and if the amount difference is <=1 and only if the previous row is the same user, i will keep the bigger number the final df will look like: username amount Nov 19, 2017 · Remove `NaN` from Pandas Dataframe by Group. We can choose to drop rows (axis=0) or columns (axis=1), and the operation can be made permanent by setting inplace=True. I have a pandas dataframe which looks like this: UNIT MACHINE. drop_duplicates is by far the least performant for the provided example. head, n=1) This is possible because by default groupby preserves the order of rows within each group, which is stable and There is a pandas dataframe on input: I need to drop all rows with items that have never been sold in particular store: pairs (1,1), (3,1) of (store_id, item_id) in the dataframe. DataFrame({'A' : ['foo', 'foo', 'bar', 'bar', 'bar'], 'B' : ['1', '2','2', '4', '1']}) Below is how I want it to look, And here is how I Dec 18, 2020 · You can see one N/A row is missing in the result, Remove `NaN` from Pandas Dataframe by Group. to delete only one particular row use. May 23, 2018 · 3. else: return False. Just to add, since 'list' is not a series function, you will have to either use it with apply df. Pandas datasets can be split into any of their objects. Criteria = pd. So a separate row should have been there in my output. filter(lambda x: x. , the group size). apply(DataFrame. first method to get the first non-null entry of each column. loc[mask] : Aug 27, 2020 · As Stated, I would like to remove a specific row based on group by logic. Before that, I got this: <pandas. Here's what I have: df['volume'] = df. I'm trying to combine multiple sets of rows together to remove duplicates in a CSV, using python and pandas. And somehow I can't make the next step and apply this to the whole group. Series. That is, it gives a count of all rows Easy solution would be to apply the idxmax() function to get indices of rows with max values. index[::-1], s. Jul 14, 2020 · Delete rows based on the quantity of the last row in the same group 0 pandas: how to drop all rows of a group if the last row of the group has certain column value Feb 5, 2019 · Using this code df. index)] counts is a pd. I have tried to use pandas filter function, but the problem is that it is operating on all rows in group at one time: How to delete the last line of a groupby. The following is the syntax: df. DataFrame(data = data,columns=headers) The value_counts method produces a dict with unique column values as the keys and a count as the value. So I want to drop row with index 4 and keep row with index 3. groupby('a'). nth(0) rather than . 5 3 k. size() size[size > 1] Doing that I get Series([], dtype: int64). txt", sep='\t') group = df. df2 = df[df. # example dataframe. DataFrame filter based on groupby. kd da fa oi yo dn fg vm bx od