Number duplicates in pandas. Before diving into how the Pandas .
Number duplicates in pandas df = df. 2 5 8. RANK based on SORT by multiple columns. The idea is to convert each zero to zero plus its position (0+1 for first row, 0+2 This guide demonstrated various techniques to detect, analyze, and remove duplicate rows in Pandas using drop_duplicates(), duplicated(), groupby(), sort_values(), count(), and unique(). Method 2: Count Duplicate Rows. all the other ones without a gigantic for loop of converting row_i toString() and then comparing it to all the Grouping by multiple columns to find duplicate rows pandas. groupby() method specifically so that I can add a new column to the dataframe which shows count of rows which are identical to the current one. value_counts(): Provides counts of each unique value in a column. drop_dupl Skip to main content. 6", it wouldn't get picked up unless there were 6 "DupeCol"s preceding "DupeCol. 1. duplicated() method, which returns a boolean Series indicating duplicated rows. duplicated(['B']). iterrows() and extracting the indices of equal entries with help of pd. drop_duplicates(subset=["num"], keep=False) Also the same I do with column age: df. Eg. Pandas dataframe: keep rows with duplicates. 518207 Bicycle theft 1 2015-01 E01000914 -0. That said, you may want to avoid introducing duplicates as part of a data processing pipeline (from methods like pandas. Count duplicates in rows In Pandas, retrieving unique values from DataFrame is used for analyzing categorical data or identifying duplicates. sort(['fullname']) I think I have to use the iterrows to do what I want as an object. Find All Duplicate Rows in a Pandas Dataframe. drop_duplicates() method works, it can be helpful to understand what options the method offers. 6", Introduction. python; pandas; for-loop; Share. copy() python: count number of duplicate entries in column. drop_duplicates(subset='Customer Number', keep=False, inplace=True) That will remove all duplicate rows from the DataFrame. Ask Question Asked 4 years, 6 months ago. im trying to count duplicates and then drop. Pandas how to get distinct rank when the you dont have unique counts. 518226 Burglary 3 2015-01 E01000914 -0. The duplicated() function returns a boolean series that indicates which rows are duplicate rows. csv', header = 0) df. Let's learn how to get unique values from a column in Pandas DataFrame. Here, inplace=True specifies that the changes are to be made in the original dataframe. duplicated(keep=False)] engineID Date 0 1133 2016-01-24 1 1133 2016-02-20 Pandas: Find duplicates and modify them based on date. The duplicated() method returns a Series with True and False values that describe which rows in the DataFrame are duplicated and not. piRSquared. duplicated()]. from. 1,777 2 2 gold badges 21 21 silver badges 34 34 bronze badges. Follow edited Nov 7, 2016 at 17:45. There are some duplicates in each column that I'd like to keep. Find duplicated rows and replace value in one column. concat(), rename(), etc. Replacing duplicate values in a dataframe. engineID. duplicated (subset = None, keep = 'first') [source] # Return boolean Series denoting duplicate rows. I use this pattern to find duplicates in column A from set duplicates: duplicates = {1, 2, 3} df[~df['A']. Removing duplicate rows in dataframe in python. drop_duplicates with keep=first: df. Pandas Dataframe duplicate rows with mean-based on the unique value in one column and so that each unique value have same number of rows. round, args=[4]), then drop the duplicates. 5 3 8. nan], ['sth diff', 'dupe row', 'x']], columns=['col1', 'col2', 'col3']) print(df) # Output: col1 col2 col3 0 whatever dupe row x 1 idx 1 import Pandas df = pandas. How to count unique values in a Pandas DataFrame? To count unique values, use the nunique() method. Adding how='inner' or 'outer' does not yield the desired result. 111497 Since we are going for most efficient way, i. E. This method returns a boolean Series indicating whether each row is a duplicate of a You can use the following methods to count duplicates in a pandas DataFrame: Method 1: Count Duplicate Values in One Column. The following code shows how to count the number of duplicate rows in the DataFrame: #count number of duplicate rows len (df)-len (df. number" convention that Pandas uses. I want to add 1,2,3 where I would like to filter rows containing a duplicate in column X from a dataframe. sum where the value count is greater than 1 . Follow edited Sep 2, 2017 at 19:51. Keep rows that are duplicates except one column in Python. to_datetime(s, unit = 'ms') # To remove the duplicates duplicatedRows = In Pandas, I can drop duplicate rows inside a database based on a single column using the. apply(np. Either all duplicates, all except the first or all except the last occurrence of duplicates can be indicated. subset should be a sequence of column labels. id val1 val2 1 1. 14. groupby(by=['n','v'], as_index=False) # Use all columns Another simple solution: Try combining columns for date and ID into a third column "date"+"ID". head tail count 134; 135; 3 134; 136; 2 134; 137; 2 Another problem is that the csv file is super big (60GB), RAM is 64G btw, if set the chunksize to some number and do the iteration like: Let us see how to count duplicates in a Pandas DataFrame. This article also briefly explains the groupby() method, which To count duplicates in a Pandas DataFrame in Python, one can utilize methods like df. How to count duplicates in Pandas? Ask Question Asked 2 years, 9 months ago. asked Sep 2, 2017 at 19:25. Please give us code that generates your dataframe, not just the text output or print. In this example, we removed duplicate entries from df using drop_duplicates(). shape >> (40473, 15) So df. How to conditionally remove duplicates from a pandas dataframe. duplicated(subset='Column_A', keep='first') Change the parameters to fine tune to your needs. One common approach is I have a DF in Pandas, which looks like: Letters Numbers A 1 A 3 A 2 A 1 B 1 B 2 B 3 C 2 C 2 I'm looking to count the number of similar rows and save the result in a third column. One workaround would be to round the data to however many decimal places are applicable with something like df. (the How can use fuzzy matching in pandas to detect duplicate rows (efficiently) How to find duplicates of one column vs. duplicated(df. Series" instead of "pandas. drop_duplicates() method: # Understanding the Pandas . Before diving into how the Pandas . The groupby is the right idea, but the right method is cumcount: >>> product_df['month_num'] = product_df. It returns the number of unique values in a column or DataFrame. drop_duplicates()) Or simply you can use DataFrame. import I want to count the number of duplicated elements in a pandas dataframe "data", specifically here in the roi column, and input this number into each corresponding row of the count column. 4. 038462 2 1 product_b If the goal is to only drop the NaN duplicates, a slightly more involved solution is needed. 018868 1 6 product_a 2014-03-01 50 -0. Modified 4 years, 6 months ago. between('2016-01-01', '2016-06-30') & df. Here is an example: import pandas as pd # create a sample dataframe df = pd. Only consider certain columns for identifying duplicates, by default use all of the columns. Both Series and DataFrame disallow duplicate labels by calling . 2 2 2. ). You can count duplicates in pandas DataFrame by using DataFrame. By default, drop_duplicates() scans the entire DataFrame for duplicate rows and removes all subsequent occurrences, retaining only the first instance being the pandas. duplicated(subset=['name'], take_last=True), 'name'] However, I think the apply function does not allow for inplace modification, right? So If N=1, I could simply use the . For a set of distinct duplicate rows, flag all but the last row as duplicated. pandas data frame: adding 'count' column for multiple occurrences on one column/ duplicates. e. Series. Count Frequency of Columns in Pandas DataFrame I'm new to Pandas and I want to merge two datasets that have similar columns. Pandas is one of those packages and makes importing and analyzing data much easier. 1 5. vc[vc. The pandas. Python is a great language for doing data analysis, primarily because of the fantastic ecosystem of data-centric Python packages. Date. drop_duplicates(subset='key', keep='last') value key something 2 c 1 4 8 d 2 10 9 a 3 5 How do I keep the last 3 rows for each unique values of key? What is the pandas way of finding the indices of identical rows within a given DataFrame without iterating over individual rows? While it is possible to find all unique rows with unique = df[df. if a user had named two columns "DupeCol" and "DupeCol. We can use the Counter from the collections module, this custom method involves converting DataFrame rows to tuples DataFrames are a powerful tool for working with data in Python, and Pandas provides a number of ways to count duplicate rows in a DataFrame. So assume I have this: col 1 | 1 2 | 2 3 | 1 4 | 1 5 | 2 I would like to count and to print duplicates per column like: A 0 B 2 C 3 D 1 I have only found to count duplicates for one column: df. If you want to keep the original data but remove rows that are duplicate up to rounding, you can use something like. If you like to count duplicates on particular column(s): len(df['one'])-len(df['one']. ‘first’ : Drop duplicates except for the first occurrence. However, if there are duplicates for a value in X, I would like to give preference to one of them based on the value of another column Y. Count the number of unique values per group. I tried the duplicate method from pandas, but it will leave only the unique items or the unique items plus the first or last duplicate. python: count number of duplicate entries in column. This poses a challenge when you want to visually inspect all occurrences of the You are right, but I dont know why groupby always output a "Pandas. (the Finding duplicates in a list is a common task in programming. drop_duplicates('foo') command. How to count duplicates in column One common task in data analysis is to count the number of duplicate values in a Pandas DataFrame. Replace values in Pandas DataFrame with Unique values from the same DataFrame. series. id letter 0 665639 AAAAAA 1 665639 AAAAAA 2 665639 AAAAAA 3 665639 AAAAAA 5 702090 BBBBBB 6 702092 CCCCCC to Few names are duplicated, and I want to append a simple indicator to the duplicates. pivot_table() function. drop_duplicates() What is the simplest way of counting the number of times each row of 'duplicates' appears in 'data'? Definition and Usage. duplicated()). pivot_table () for aggregating duplicate You can count duplicates in pandas DataFrame by using DataFrame. Count duplicates in rows per column in pandas DataFrame. To manage duplicates effectively, we first I would like to create unique identifiers for values that are duplicates. duplicated() == True)] show that there are duplicate rows but groupby doesn't. Below are the examples by which we can select duplicate rows in a DataFrame: Select Duplicate Rows Based on All Columns; Get List of Duplicate Last Rows Based on All Columns; Select List Of Duplicate Rows Using Single Columns; Select List Of Duplicate Rows Using Multiple Columns I think I get the reason why you got discrepancy of the 2 counts from postgres and from Pandas. drop_duplicates() Both return the following: bio center outcome 0 1 one f 2 1 two f 3 4 three f Take a look at the df. First, sort on A, B, and Col_1, so NaNs are moved to the bottom for each group. This function counts the number of duplicate entries in a single column, or multiple To effectively find duplicates in pandas using Python, the duplicated () method with various parameters has been utilized. To count the number of duplicate rows in a Pandas DataFrame, use the DataFrame's duplicated(~) method. DataFrame({'n': ['a', 'a', 'a'], 'v': [1,2,1]}) >>> d n v 0 a 1 1 a 2 2 a 1 I would like to understand how to use . keep {‘first’, ‘last’, False}, default ‘first’ Determines which duplicates (if any) to keep. I've tried to use groupby for the ID that may be duplicated, and then value_counts to count. In this blog post, we will delve into the world of data manipulation using Pandas, a powerful and easy-to-use data analysis library for Python. , 'jones a' 'jones a' # this should become 'jones a2' To get the subset of duplicates, I could do . In this article, we’ll explore a few of the most common methods and highlight their advantages and disadvantages. Get count of duplicated values per category/group in Understanding the Pandas drop_duplicates() Method. df[df. result looks like the following. Get the Unique Values of Pandas using unique()The. Example: print df Month LSOA code Longitude Latitude Crime type 0 2015-01 E01000916 -0. Ask Question Asked 7 years, 4 months ago. To find duplicate rows in a pandas dataframe, we can use the duplicated() function. DataFrame([['whatever', 'dupe row', 'x'], ['idx 1', 'uniq row', np. Method Let us see how to count duplicates in a Pandas DataFrame. DataFrame. join(df2, on='Col') gives KeyError: 'Col' # Check for duplicates. 295k 65 65 gold badges 504 Tackling duplicates is a critical step in data preprocessing. Duplicated values are indicated as True values in the resulting Series. 2 4 1. In this case I used np. Use the subset parameter to specify which columns to include when looking for duplicates. cumcount() >>> product_df product_desc activity_month prod_count pct_ch month_num 0 product_a 2014-01-01 53 NaN 0 3 product_a 2014-02-01 52 -0. Notice that the drop_duplicates() function keeps the first duplicate entry and removes the last by default. Parameters: subset column label or sequence of labels, optional. Improve this answer. It is useful for identi Pandas drop_duplicates() method helps in removing duplicates from the Pandas Dataframe allows to remove duplicate rows from a DataFrame, either based on all columns or specific ones in python. I have a dataframe with duplicate rows >>> d = pd. duplicated(subset=None, Most simple way to find duplicate rows in DataFrame is by using the duplicated () method. Expected number of jigsaw puzzle Seeing as the colMap contains all of the names of the columns, duplicates or not, this will ensure that we're not grabbing a user-named column that managed to overlap with the ". Follow answered Apr I'm trying to count the number of duplicate values based on set of columns in a DataFrame. duplicated()] and then iterating over the unique entries with unique. But with NumPy slicing we would end up with one-less array, so we need to concatenate with a True element at the start to select the first element and hence we I would like to be able to get the indices of all the instances of a duplicated row in a dataset without knowing the name and number of columns beforehand. Under a single column : Find All Duplicate Rows in a Pandas Dataframe. In this example, Order is duplicated once. Pandas duplicated() returns a boolean Series. Building off Create a column which gives the number of times a values is duplicated. 1 2. The columns are going to each have some unique values compared to the other column, in addition to many identical values. How to count duplicates in Pandas? Hot Network Questions KVM doesn’t work with Iptables Tabular So I want to drop a specific number of duplicates rows. This approach covers detecting duplicate rows across I'm hoping to get the output in the following format: Name of column: Total number of duplicates in the column. We can see from the %%timeit comparison for 5 columns of 1M rows, . Below are the examples by which we can select duplicate rows in a DataFrame: Select You can use the duplicated () function to find duplicate values in a pandas DataFrame. I start with a df that has one dupe row: import pandas as pd import numpy as np df = pd. duplicated() method is used to find duplicate rows in a DataFrame. drop_duplicates documentation for syntax details. Extracting duplicate rows with loc. read_csv('csvfile. Modified 2 years, 9 months ago. where(), what is the pandas way of doing . Pandas -> DataFrame -> rank. It returns a boolean array where duplicates are marked as True based on the specified criteria and False denotes unique values or the first occurrence of duplicates. How do I rank values of Pandas row into separate dataframe? 0. I tried with this code but is taking ages: Their execution time is not really affected by number of columns while mine scales linearly with number of columns as well as number of rows. Viewed 81k times 40 . Replace duplicate value and want the duplicate rows (on head and tail columns) to be count and add the count together. Now you can use count to find the number of duplicates for each entry in the new 3rd column. ix[~df. Viewed 122 times python: count number of duplicate entries in column. If you’re working with datasets in Python using the Pandas library and need to identify duplicate entries present in a DataFrame, you might have encountered the limitation of df. Detecting Duplicates. # To get some time conversion s = pd. 106453 51. 2. I'm wondering if there is a way to catch this data in another table for independent review. loc[df. Hot Network Questions Can a water elemental attack you while you are whelmed? As noted above, handling duplicates is an important feature when reading in raw data. unique()method returns a NumPy array. 17: We can play with the take_last argument of the duplicated() method: take_last: boolean, default False. If you want to keep the first or last row which contains a duplicate, change keep to first or last. drop_duplicates ()) 2. sum() We can see that there are 4 duplicate values in the points column. However, I keep getting the wrong answer (2 but in excel it's print(df) Output. gt(1)] creates a pandas. duplicated (keep = 'first') [source] # Indicate duplicate Series values. There are different ways to count duplicates in a Pandas DataFrame, depending on the specific requirements of the analysis. You will also get to know a few practical tips for using this method. It returns a boolean series which identifies whether a row is duplicate or unique. Under a single column : We will be using the pivot_table() function to count the duplicates in a single column. 0. round, args=[4]). Ask Question Asked 5 years, 8 months ago. drop_duplicates()) If you want to count duplicates on entire dataframe: len(df)-len(df. Counter function. My desired output is shown below. 2 1 1. Replace the values of all duplicate rows in Python Pandas. count number of duplicate entries in column. drop_duplicates(subset=['bio', 'center', 'outcome']) Or in this specific case, just simply: df. 2 min read. duplicated() == True)] print duplicates. The column in which the duplicates a. My data consist of strings, integers, floats and nan. We then index the df with this boolean array to find the duplicate row: df_all = df_all. groupby() will generate the count of a number of occurrences of data present in a particular column of the dataframe. Ranking with no duplicates. isin(duplicates)] It works and returns me rows witout duplicates. The column in which the duplicates are to be found will be passed as the value of the index parameter. Replace or Update Duplicate Values. These functions return the length or count of the total number of duplicate single rows in a dataframe. It's because of your code to filter duplicated entries: newdf = healthdf[healthdf. EDIT. sum() 77 3. The second method for handling I'm interested in assigning values to duplicate rows in a Pandas dataframe as below. Pandas provides the . Then call df. does [1, 2, 3, 3, 3] have a duplicate count of 1 or 2? – This tutorial will guide you through various methods of identifying and removing duplicate rows using Pandas, applicable from basic to advanced use cases. By default, the method marks all but the first occurrence of duplicates as True. Improve this question. sum() Do I have to write all columns (about 30) or is it possible to use something from pandas? I have tried this but it doesn't work: df. Example 2: Count Duplicate Rows. where() and df. duplicated(), which by default only marks the first occurrence of duplicate values. df['Column_B'] = df. DataFrame" – Yippee. We can see that there are 2 duplicate rows in the DataFrame. Follow asked Jul 30, 2018 at 6:33. to_numeric(mydataset['timestamp'], errors = 'coerce') + local mydataset['timestamp'] = pd. Using pandas dataframe to output rank in sorted order. drop_duplicates() and df[(df. For instance, roi 35 appears twice, hence each of the rows in the count column should have a "2". Series with the counts, for each value in a column, that're greater than 1. Pandas finding duplicated elements. Before we dive into the examples, make sure that you have Pandas installed and imported in your environment: import pandas as pd Identifying Duplicate Rows. In Python, there are several ways to do this. For a (100000,300) DataFrame with no duplicates, pandas. Let’s create a simple dataset to illustrate Drop consecutive duplicates in Pandas dataframe if repeated more than n times. I'm trying to see the maximum number of duplicates for any record. If we set take_last's value to True, we flag all Only consider certain columns for identifying duplicates, by default use all of the columns. This method is especially useful for data cleaning and preprocessing, ensuring that your data is free As noted above, handling duplicates is an important feature when reading in raw data. 3. I'm trying to remove duplicates values in ID column, count the duplicates in the ID column and create a new column called Count, and concatenate the Axis column THIS IS MY CURRENT DATAFRAME: ID To identify duplicates within a pandas column without dropping the duplicates, try: Let 'Column_A' = column with duplicate entries 'Column_B' = a true/false column that marks duplicates in Column A. Example: Detecting Duplicates in a Simple Dataset. g. Pandas find the duplicate data. Let’s first take a look at the different parameters and default arguments in the Pandas . Our task is to count the number of duplicate entries in a single column and multiple columns. drop_duplicates(subset='Customer Number', keep=False) Or the equivalent: df_all. Only Retain Unique Duplicates from Pandas Replacing specific column values after removing duplicates in a pandas dataframe. drop_duplicates() function as such: >>> df. how to join two dataframe Pandas way to make new column that index matches a key for all duplicate values in another column 0 Duplicates using python, if any create a new column when there's a match However, I am not able to calculate number of duplicates for each unique row of data and insert counts into a new column. Values that are duplicates are only 0's. Pandas provides a very straightforward way to identify duplicate rows in a dataset using the duplicated() method. 2 I want to group by val1 and val2 and get similar dataframe only with rows which has How to Detect Duplicates in Pandas. data. I'm not concerned with anything that is not a duplicate. (Helps make this reproducible) python: count number of duplicate entries in column. drop_duplicates Method import Futhermore, I can find the duplicate rows doing the following: duplicates = df[(df. Count For versions preceding Pandas 0. groupby('product_desc'). This function uses the following basic syntax: #find duplicate rows across specific In pandas, the duplicated() method is used to find, extract, and count duplicate rows in a DataFrame, while drop_duplicates() is used to remove these duplicates. set_flags(allows_duplicate_labels=False). False: Drop all duplicates. We can then filter the dataframe using this boolean series to get all the duplicate rows. duplicated () for marking duplicates, groupby () combined with size () for counting occurrences, df. Share. This can be done by getting the pandas. value_counts for each column, and then get the pandas. The dataframe is below:- data_1 = {'ID': ['001', '003', '001','002','002','002 I have a DataFrame which contains many duplicates of rows and I would like to count the number of times each duplicate appears in the table. duplicated() method in Pandas is a powerful tool for identifying duplicate values within an index. cuplicates to get dataframe without duplicates but heve extra col in which we have number that represents how many duplicates there were. I have a df. loc[:,:]). df. Pandas count duplicate rows using a custom function with collections. Remove duplicates by dropping with drop_duplicates() or by groups after The second determines if there are duplicates. duplicated()] The Index. To find the duplicates, I use drop_duplicates: duplicates = data. This method checks each row against the others and returns a boolean Series indicating whether the row is a duplicate. Counting max number of duplicates with pandas. What return print (df['Col Merging two DataFrames with different number of key elements in Pandas. Pandas duplicated() and drop_duplicates() are two quick and convenient drop_duplicates(): Removes duplicate values, returning either a DataFrame or Series. 8 6. Using the size() or count() method with pandas. Viewed 362 times 0 . This function counts the number of duplicate entries in a single column, or multiple columns, and counts duplicates when StudentName Score 1 Ali 65 2 Bob 76 3 John 44 4 Johny 39 5 Mark 45 In the above example, the first entry was deleted since it was a duplicate. Hot Network Questions What songs did Frankenstein's Pandas - Compare each row with one another across dataframe and list the amount of duplicate values Hot Network Questions lvm2: add extra disk to a specific filesystem directory inside logical volume? It's not clear what you mean by "count of the duplicated identifier", because in your example there are always the same number of different identifiers duplicated as there are rows which are duplicates of a previous row. . I rewrote my question here to be more precise about the result I want. 111497 51. techscolasticus techscolasticus. duplicated() and assigned any count> 4 to be NaN. How to count duplicates in Pandas? 0. We will slice one-off slices and compare, similar to shifting method discussed earlier in @EdChum's post. The problem with dropping duplicates is that I will lose the amount or the amount may be different. For example, the output I'm looking for: Let us see how to count duplicates in a Pandas DataFrame. Commented May 16, 2019 at 2:23. The key steps are: Check for duplicates with duplicated() and filter the DataFrame to extract them. reservoirinvest reservoirinvest. By default, the first occurrence of two or more duplicates will be set to False. Modified 5 years, 8 months ago. pandas; Share. 518226 Burglary 2 2015-01 E01000914 -0. core. Default is for all but the first row to be flagged. frame. However, this If you want to count the number of non-duplicates (The number of False), you can invert it with negation (~)and then call sum(): # Count the number of non-duplicates >>> (~df. I'd like my final output to look like this: Groupby and count the number of unique values (Pandas) 0. Handling Duplicate Values in a Pandas DataFrame. By default, drop_duplicates() scans the entire DataFrame for duplicate rows and removes all subsequent occu I have a data frame like this: df: col1 col2 1 pqr 3 abc 2 pqr 4 xyz 1 pqr I found that there is duplicate value and its pqr. >>> dd = d. Mean value of 2 group by's if value is not unique pandas. Considering certain columns is optional. Modified 1 year, 11 months ago. Let’s explore the efficient methods to find duplicates. techscolasticus. Let me explain by an example : A B C 0 foo 2 3 1 foo nan 9 2 foo 1 4 3 bar 8 nan 4 xxx 9 10 5 xxx 4 4 6 xxx 9 6 So we have duplicated rows based on column A, so for 'foo' I want to drop 2 duplicates rows for example and for 'xxx' I want to drop just one row. ‘last’ : Drop duplicates except for the last occurrence. By default all columns are included. Average values on duplicate records. Viewed 2k times 2 . Duplicates can occur when multiple rows have the same values in all columns, or in a subset of columns. I want to find how many times IDField 20 in Frame 10_01 has duplicates in Order. python; pandas; dataframe; duplicates; Share. apply with vectorized methods, as well as Pandas drop_duplicates() method helps in removing duplicates from the Pandas Dataframe allows to remove duplicate rows from a DataFrame, either based on all columns or specific ones in python. Using a Set (Most Efficient for Large Lists)Set() method is used to set a track seen elements and helps to identify duplicates. Name Age City 0 John 28 New York 1 Anna 24 Los Angeles 4 John 19 Chicago. duplicated# Series. performance, let's use array data to leverage NumPy. In this article, you will learn how to use this method to identify the duplicate rows in a DataFrame. Removing duplicates from Pandas dataFrame with condition for retaining original. df1. duplicated# DataFrame. [GFGTABS So I remove the duplicates: df. gkpsuqubiimtvkelicndzueafyumwuqyattcekppnfsqgebcknbvpeprcutrneyvnjecavmdmnv
