PySpark supports various UDFs and APIs to allow users to execute Python native functions. CTE), 01:Data Backfilling interview questions & answers. Create PySpark DataFrame from list of tuples, Extract First and last N rows from PySpark DataFrame. How to name aggregate columns in PySpark DataFrame ? After doing this, we will show the dataframe as well as the schema. you can also provide options like what delimiter to use, whether you have quoted data, date formats, infer schema, and many more. We can use list comprehension for looping through each row which we will discuss in the example. dfFromData2 = spark.createDataFrame(data).toDF(*columns), regular expression for arbitrary column names, * indicates: its passing list as an argument, What is significance of * in below left to right) for each level as shown below. Similarly you can also create a DataFrame by reading a from Text file, use text() method of the DataFrameReader to do so. You can also create PySpark DataFrame from data sources like TXT, CSV, JSON, ORV, Avro, Parquet, XML formats by reading from HDFS, S3, DBFS, Azure Blob file systems e.t.c.if(typeof ez_ad_units != 'undefined'){ez_ad_units.push([[320,50],'sparkbyexamples_com-box-3','ezslot_9',105,'0','0'])};__ez_fad_position('div-gpt-ad-sparkbyexamples_com-box-3-0');if(typeof ez_ad_units != 'undefined'){ez_ad_units.push([[320,50],'sparkbyexamples_com-box-3','ezslot_10',105,'0','1'])};__ez_fad_position('div-gpt-ad-sparkbyexamples_com-box-3-0_1'); .box-3-multi-105{border:none !important;display:block !important;float:none !important;line-height:0px;margin-bottom:7px !important;margin-left:auto !important;margin-right:auto !important;margin-top:7px !important;max-width:100% !important;min-height:50px;padding:0;text-align:center !important;}, Finally, PySpark DataFrame also can be created by reading data from RDBMS Databases and NoSQL databases.if(typeof ez_ad_units != 'undefined'){ez_ad_units.push([[320,50],'sparkbyexamples_com-medrectangle-3','ezslot_11',156,'0','0'])};__ez_fad_position('div-gpt-ad-sparkbyexamples_com-medrectangle-3-0');if(typeof ez_ad_units != 'undefined'){ez_ad_units.push([[320,50],'sparkbyexamples_com-medrectangle-3','ezslot_12',156,'0','1'])};__ez_fad_position('div-gpt-ad-sparkbyexamples_com-medrectangle-3-0_1'); .medrectangle-3-multi-156{border:none !important;display:block !important;float:none !important;line-height:0px;margin-bottom:7px !important;margin-left:auto !important;margin-right:auto !important;margin-top:7px !important;max-width:100% !important;min-height:50px;padding:0;text-align:center !important;}. how would I convert the dataframe to an numpy array? In type systems, you can define types recursively. The number of rows to show can be controlled via spark.sql.repl.eagerEval.maxNumRows configuration. lightGBM3:PySparkStringIndexerpipeline. There is one weird edge case - it is possible to have LESS than 4 professors or students for a given time frame. at any one time frame, there is at most 4 professors and 4 students. @Chirag: I don't think there is any easy way you can do it. This method is used to iterate row by row in the dataframe. Filtering a row in PySpark DataFrame based on matching values from a list. Series within Python native function. When and how was it discovered that Jupiter and Saturn are made out of gas? let me know if this works for your task. the desired is_match column should have assigned==student: Step-4: use join to convert student back to student_id (use broadcast join if possible): As our friend @cronoik mention you need to use Hungarian algorithm, the best code I saw for unbalance assignment problem in python is: Redshift RSQL Control Statements IF-ELSE-GOTO-LABEL. By clicking Post Your Answer, you agree to our terms of service, privacy policy and cookie policy. upgrading to decora light switches- why left switch has white and black wire backstabbed? CSV is straightforward and easy to use. This notebook shows the basic usages of the DataFrame, geared mainly for new users. Asking for help, clarification, or responding to other answers. you can use json() method of the DataFrameReader to read JSON file into DataFrame. Does the double-slit experiment in itself imply 'spooky action at a distance'? StringIndexerStringIndexer . In the question, I mentioned a recursive algorithm because this is a traditional recursive type problem, but if there is a quicker solution that doesn't use recursion I am open to that. In most of hierarchical data, depth is unknown, you could identify the top level hierarchy of one column from another column using WHILE loop and recursively joining DataFrame. the students might still be s1, s2, s3, s4. Are there conventions to indicate a new item in a list? In the given implementation, we will create pyspark dataframe using a list of tuples. Should I use lag and lead functions? How to get a value from the Row object in PySpark Dataframe? This method will collect all the rows and columns of the dataframe and then loop through it using for loop. We would need this rdd object for all our examples below. Filter Pyspark dataframe column with None value, Show distinct column values in pyspark dataframe, Need to extract the data based on delimiter and map to data frame in pyspark. Note: This function is similar to collect() function as used in the above example the only difference is that this function returns the iterator whereas the collect() function returns the list. PySpark applications start with initializing SparkSession which is the entry point of PySpark as below. How to change dataframe column names in PySpark? createDataFrame() has another signature in PySpark which takes the collection of Row type and schema for column names as arguments. Common Table Expression) as shown below. For each time frame, I need to find the one to one pairing between professors/students that maximizes the overall score. After doing this, we will show the dataframe as well as the schema. Thanks for contributing an answer to Stack Overflow! The EmpoweringTech pty ltd has the right to correct or enhance the current content without any prior notice. Once UDF created, that can be re-used on multiple DataFrames and SQL (after registering). rev2023.3.1.43266. This previous question could give you some idea how to do it approximately though: If you showed us the whole table and it really is "small enough", i would not use spark to calculate. You can try pandas_udf and scipy.optimize.linear_sum_assignment(note: the backend method is the Hungarian algorithm as mentioned by @cronoik in the main comments), see below: Step-0: add an extra column student, and create a new dataframe df3 with all unique combos of time + student_id + student. Here the initial code to generate the sample datasets: I was able to get the first removal for the child turbofan with the below code : How can I create a for loop or a recursive loop within the part_change_df to get the results like this that takes each parent of the first child and makes it the next child and get the first removal information after the first child(turbofan)'s maintenance date)? Rename PySpark DataFrame Column Methods and Examples, Replace Pyspark DataFrame Column Value Methods. How to add column sum as new column in PySpark dataframe ? Example: In this example, we are going to iterate three-column rows using iterrows () using for loop. For this, we are creating the RDD by providing the feature values in each row using the parallelize() method and added them to the dataframe object with the schema of variables(features). PySpark DataFrames are lazily evaluated. The part change dataframe stores all part removals for all the helicopter parts, parent(rotor), and child (turbofan, axle, module). We can use toLocalIterator(). Not the answer you're looking for? Spark SQL and Dataset Hints Types- Usage and Examples, How to Remove Duplicate Records from Spark DataFrame Pyspark and Scala, Spark SQL to_date() Function Pyspark and Scala. The rows can also be shown vertically. GraphX is a new component in a Spark for graphs and graph-parallel computation. For this, we are providing the feature values in each row and added them to the dataframe object with the schema of variables(features). These are general advice only, and one needs to take his/her own circumstances into consideration. Another example is DataFrame.mapInPandas which allows users directly use the APIs in a pandas DataFrame without any restrictions such as the result length. The select() function is used to select the number of columns. The pyspark.sql.SparkSession.createDataFrame takes the schema argument to specify the schema of the DataFrame. for a single day, there will be up to 14 professors and 14 students to choose from. Can an overly clever Wizard work around the AL restrictions on True Polymorph? For this, we are providing the list of values for each feature that represent the value of that column in respect of each row and added them to the dataframe. A-143, 9th Floor, Sovereign Corporate Tower, We use cookies to ensure you have the best browsing experience on our website. It is an alternative approach of Teradata or Oracle recursive query in Pyspark. This method is used to iterate row by row in the dataframe. What is the ideal amount of fat and carbs one should ingest for building muscle? Derivation of Autocovariance Function of First-Order Autoregressive Process. After doing this, we will show the dataframe as well as the schema. What are some tools or methods I can purchase to trace a water leak? Please refer PySpark Read CSV into DataFrame. So these all are the methods of Creating a PySpark DataFrame. The only difference is that collect() returns the list whereas toLocalIterator() returns an iterator. Get statistics for each group (such as count, mean, etc) using pandas GroupBy? What does in this context mean? This is useful when rows are too long to show horizontally. Why is the article "the" used in "He invented THE slide rule"? In this article, we will discuss how to iterate rows and columns in PySpark dataframe. Alternatively, you can enable spark.sql.repl.eagerEval.enabled configuration for the eager evaluation of PySpark DataFrame in notebooks such as Jupyter. How to split a string in C/C++, Python and Java? PySpark DataFrame also provides the conversion back to a pandas DataFrame to leverage pandas API. Python pd_df = df.toPandas () for index, row in pd_df.iterrows (): print(row [0],row [1]," ",row [3]) Making statements based on opinion; back them up with references or personal experience. Asking for help, clarification, or responding to other answers. Before that, we have to convert our PySpark dataframe into Pandas dataframe using toPandas() method. You are trying to model relationships between friends, probably the best way to work with this would be using Graphs. Drift correction for sensor readings using a high-pass filter. Asking for help, clarification, or responding to other answers. How to split a string in C/C++, Python and Java? PySpark DataFrame is lazily evaluated and simply selecting a column does not trigger the computation but it returns a Column instance. How to duplicate a row N time in Pyspark dataframe? Why was the nose gear of Concorde located so far aft? For example, DataFrame.select() takes the Column instances that returns another DataFrame. you just need to convert your DataFrame into Numpy array and pass to the KM_Matcher then add a column with withColumn function in spark depend on your answer from KM_Matcher. The relational databases use recursive query to identify the hierarchies of data, such as an organizational structure, employee-manager, bill-of-materials, and document hierarchy. pyspark.sql.SparkSession.createDataFrame takes the schema argument to specify the schema of the DataFrame. The iterrows () function for iterating through each row of the Dataframe, is the function of pandas library, so first, we have to convert the PySpark Dataframe into Pandas Dataframe using toPandas () function. Spark Recursion Edit: As discussed in comments, to fix the issue mentioned in your update, we can convert student_id at each time into generalized sequence-id using dense_rank, go through Step 1 to 3 (using student column) and then use join to convert student at each time back to their original student_id. https://databricks.com/blog/2016/03/03/introducing-graphframes.html. document.getElementById( "ak_js_1" ).setAttribute( "value", ( new Date() ).getTime() ); What is significance of * in below use the show() method on PySpark DataFrame to show the DataFrame. yes SN is always unique , its like you have tyre wheel assembly and car, the tyre is always same and it moves between wheel assemblies and the wheel assemblies moves between cars. Spark SQL does not support recursive CTE as discussed later in this post. @LaurenLeder, I adjusted the pandas_udf function to handle the issue when # of processors are less than 4. also the NULL value issues, all missing values from the 4*4 matrix feed to linear_sum_assignment will be zeroes. Spark add new column to dataframe with value from previous row, pyspark dataframe filter or include based on list, How to change case of whole pyspark dataframe to lower or upper, Access a specific item in PySpark dataframe, Add column to Pyspark DataFrame from another DataFrame, Torsion-free virtually free-by-cyclic groups. The ultimate goal is like to get the child maintenance date and roll up all the way to the final parent removal date and the helicopter serial no: Thanks for contributing an answer to Stack Overflow! Note that, it is not an efficient solution, but, does its job. Site design / logo 2023 Stack Exchange Inc; user contributions licensed under CC BY-SA. Find centralized, trusted content and collaborate around the technologies you use most. The contents in this Java-Success are copyrighted and from EmpoweringTech pty ltd. Parquet and ORC are efficient and compact file formats to read and write faster. In real-time mostly you create DataFrame from data source files like CSV, Text, JSON, XML e.t.c. Ackermann Function without Recursion or Stack. I could hardcode each parent and join working dataframe with the part change dataframe, but the problem i don't know exactly how high the number of parents a child will have . Applications of super-mathematics to non-super mathematics. https://databricks.com/blog/2016/03/03/introducing-graphframes.html, The open-source game engine youve been waiting for: Godot (Ep. Why does RSASSA-PSS rely on full collision resistance whereas RSA-PSS only relies on target collision resistance? This method will collect rows from the given columns. Note that toPandas also collects all data into the driver side that can easily cause an out-of-memory-error when the data is too large to fit into the driver side. It can be a boolean or a 0/1 bit or whatever works. The complete code can be downloaded fromGitHub. This tutorial extends Getting started with Databricks. How to use getline() in C++ when there are blank lines in input? @cronoik - there will be at most 4 students and 4 professors per row and for each row we calculate a value for a professor student pair. To use this first we need to convert our data object from the list to list of Row. Use csv() method of the DataFrameReader object to create a DataFrame from CSV file. getchar_unlocked() Faster Input in C/C++ For Competitive Programming, Problem With Using fgets()/gets()/scanf() After scanf() in C. Differentiate printable and control character in C ? Ideally, I would like this to be as efficient as possible as there will be millions of rows. acknowledge that you have read and understood our, Data Structure & Algorithm Classes (Live), Data Structure & Algorithm-Self Paced(C++/JAVA), Full Stack Development with React & Node JS(Live), GATE CS Original Papers and Official Keys, ISRO CS Original Papers and Official Keys, ISRO CS Syllabus for Scientist/Engineer Exam, How to Iterate over rows and columns in PySpark dataframe. my 2 cents. rev2023.3.1.43266. getchar_unlocked() Faster Input in C/C++ For Competitive Programming, Problem With Using fgets()/gets()/scanf() After scanf() in C. Differentiate printable and control character in C ? PySpark applications start with initializing SparkSession which is the entry point of PySpark as shown below. by storing the data as JSON. How do I add a new column to a Spark DataFrame (using PySpark)? is this the most efficient way to do this with pyspark, Implementing a recursive algorithm in pyspark to find pairings within a dataframe, https://github.com/mayorx/hungarian-algorithm, The open-source game engine youve been waiting for: Godot (Ep. # Simply plus one by using pandas Series. What are the consequences of overstaying in the Schengen area by 2 hours? How to change dataframe column names in PySpark? How to draw a truncated hexagonal tiling? In a recursive query, there is a seed statement which is the first query and generates a result set. In the given implementation, we will create pyspark dataframe using CSV. The EmpoweringTech pty ltd will not be held liable for any damages caused or alleged to be caused either directly or indirectly by these materials and resources. For this, we are opening the JSON file added them to the dataframe object. Relational databases such as Teradata, Snowflake supports recursive queries in the form of recursive WITH clause or recursive views. I have the following two Dataframes that stores diagnostic and part change for helicopter parts. A PySpark DataFrame can be created via pyspark.sql.SparkSession.createDataFrame typically by passing a list of lists, tuples, dictionaries and pyspark.sql.Row s, a pandas DataFrame and an RDD consisting of such a list. Example: Here we are going to iterate all the columns in the dataframe with collect() method and inside the for loop, we are specifying iterator[column_name] to get column values. first, lets create a Spark RDD from a collection List by calling parallelize() function from SparkContext . Note that, it is not an efficient solution, but, does its job. To learn more, see our tips on writing great answers. 'a long, b double, c string, d date, e timestamp'. for example, for many time frames in a row it might be the same 4 professors and 4 students, but then it might be a new professor (, @jxc the reason I realized that I don't think I clarified this/was wondering if it would still work was because I saw in step 1 as the last part we got a list of all students but that list would encompass students who were not considered in a particular time frame. Why does pressing enter increase the file size by 2 bytes in windows. Torsion-free virtually free-by-cyclic groups. After selecting the columns, we are using the collect() function that returns the list of rows that contains only the data of selected columns. It is an alternative approach of Teradata or Oracle recursive query in Pyspark. Making statements based on opinion; back them up with references or personal experience. Browse other questions tagged, Where developers & technologists share private knowledge with coworkers, Reach developers & technologists worldwide, i only see two ways of going about this,1) combination of window functions with array/higher order functions (spark2.4+). Create a PySpark DataFrame from a pandas DataFrame. Currently spark does not support recursion like you can use in SQL via Common Table Expression. How is "He who Remains" different from "Kang the Conqueror"? 24: PySpark with Hierarchical Data on Databricks, "SELECT b.node_id, b.parent_node_id FROM {} a INNER JOIN node_rec b ON a.node_id = b.parent_node_id", "SELECT node_id, parent_node_id from vt_level_{}", " union select node_id, parent_node_id from vt_level_{}", 300+ Java Enterprise Edition Interview Q&As, https://community.cloud.databricks.com/login.html, 6 Delta Lake interview questions & answers, 25: PySpark SQL With Common Table Expression (i.e. How to print size of array parameter in C++? Step 1: Login to Databricks notebook: The level-0 is the top parent. Why does RSASSA-PSS rely on full collision resistance whereas RSA-PSS only relies on target collision resistance? Method 3: Using iterrows () This will iterate rows. PySpark DataFrame also provides a way of handling grouped data by using the common approach, split-apply-combine strategy. By default, the datatype of these columns infers to the type of data. Step 5: Combine the above 3 levels of dataframes vt_level_0, vt_level_1 and vt_level_2. To learn more, see our tips on writing great answers. If you wanted to specify the column names along with their data types, you should create the StructType schema first and then assign this while creating a DataFrame. my server has SciPy version 1.2.0 which does not support this parameter, so just left the old logic as-is. From a list, it is an alternative approach of Teradata or Oracle recursive in. Most 4 professors or students for a given time frame the given implementation, we use to. A row in the DataFrame shows the basic usages of the DataFrame as well as the schema to... References or personal experience approach, split-apply-combine strategy datatype of these columns infers to the of! So just left the old logic as-is a Spark DataFrame ( using PySpark?... Geared mainly for new users names as arguments to model relationships between friends, probably the best browsing on... Used to iterate rows supports recursive queries in the DataFrame to an numpy array types! Apis to allow users to execute Python native functions choose from Conqueror '' lazily evaluated and simply selecting a does... Or personal experience the pyspark dataframe recursive pty ltd has the right to correct or the. Own circumstances into consideration weird edge case - it is possible to have LESS than 4 or... Takes the column instances that returns another DataFrame Conqueror '' a given time,... Can enable spark.sql.repl.eagerEval.enabled configuration for the eager evaluation of PySpark as shown below True Polymorph to execute Python native.. A Spark for graphs and graph-parallel computation the top parent Sovereign Corporate,... ) in C++ that Jupiter and Saturn are made out of gas object from the row object in PySpark column... Back to a pandas DataFrame using toPandas ( ) method new column to a pandas DataFrame without prior. In C++ when there are blank lines in input from a collection by... Pyspark DataFrame the technologies you use most show can be re-used on multiple DataFrames and SQL ( after )! Readings using a high-pass filter DataFrame from list of tuples are there conventions to indicate a new in. And last N rows from the given implementation, we will create PySpark DataFrame from CSV file to ensure have! Might still be s1, s2, s3, s4 clever Wizard work around the technologies you most... Spark for graphs and graph-parallel computation ) in C++ get a value from the list toLocalIterator. Our website array parameter in C++ rename PySpark DataFrame based on opinion ; them... Difference is that collect ( ) function is used to select the number pyspark dataframe recursive rows by default, the game. Whereas toLocalIterator ( ) method have LESS than 4 professors or students for single! Works for your task: using iterrows ( ) method of the DataFrame conventions to indicate a new item a. Pyspark.Sql.Sparksession.Createdataframe takes the collection of row has the right to correct or enhance the current without... That Jupiter and Saturn are made out of gas server has SciPy version 1.2.0 which does not support recursion you! One needs to take his/her own circumstances into consideration as Teradata, Snowflake supports recursive queries in the DataFrame create... Consequences of overstaying in the given implementation, we are going to iterate row by row in example. @ Chirag: I do n't think there is any easy way you can in!, and one needs to take his/her own circumstances into consideration to get value. We have to convert our PySpark DataFrame using a high-pass filter, split-apply-combine.! Notebook shows the basic usages of the DataFrameReader object to create a Spark from... Returns a column does not trigger the computation but it returns a column instance when!, e timestamp ' stores diagnostic and part change for helicopter parts show can be a or. Logo 2023 Stack Exchange Inc ; user contributions licensed under CC BY-SA whatever works distance ' whereas. Creating a PySpark DataFrame column value Methods example is DataFrame.mapInPandas which allows directly..., b double, c string, d date, e timestamp ' various UDFs APIs. Just left the old logic as-is first and last N rows from list... Dataframe object, geared mainly for new users Table Expression an overly clever work... As count, mean, etc ) using for loop possible as there be. On matching values from a collection list by calling parallelize ( ) another! Returns a column instance policy and cookie policy based on matching values from list! The overall score Creating a PySpark DataFrame also provides the conversion back to a Spark rdd from collection! Corporate Tower, we will create PySpark DataFrame from CSV file c,! Allow users to execute Python native functions open-source game engine youve been waiting for: Godot ( Ep when! Conqueror '' supports recursive queries in the DataFrame and then loop through it using loop!, Text, JSON, XML e.t.c toLocalIterator ( ) has another in! Still be s1, s2, s3, s4 bit or whatever works the level-0 is article... There conventions to indicate a new item in a Spark for graphs and graph-parallel.! Teradata, Snowflake supports recursive queries in the given implementation, we going. Data Backfilling interview questions & answers ( Ep as count, mean etc. Are general advice only, and one needs to take his/her own circumstances into consideration or. 4 professors and 14 students to choose from to indicate a new column to a pandas to. Levels of DataFrames vt_level_0, vt_level_1 and vt_level_2 up with references or personal experience was the nose gear of located. Supports recursive queries in the given implementation, we will show the DataFrame to leverage API! When there are blank lines in input: in this article, we create. Timestamp ' rdd object for all our examples below the type of data gear Concorde... Are general advice only, and one needs to take his/her own circumstances into consideration https: //databricks.com/blog/2016/03/03/introducing-graphframes.html the. Numpy array, Extract first and last N rows from PySpark DataFrame data... Each group ( such as Teradata, Snowflake supports recursive queries in the Schengen by. 14 students to choose from pyspark dataframe recursive computation systems, you can do it '' used ``! Think there is a new component in a recursive query in PySpark DataFrame the eager evaluation of PySpark DataFrame takes... Find the one to one pairing between professors/students that maximizes the overall score object from the list list... Use CSV ( ) function from SparkContext, etc ) using for loop or enhance the current without! Wizard work around the AL restrictions on True Polymorph collect ( ) returns the whereas... Content without any restrictions such as Jupyter the Common approach, split-apply-combine strategy to get value., XML e.t.c DataFrame, geared mainly for new users model relationships between friends, probably best! Also provides the conversion back to a Spark for graphs and graph-parallel computation all the and... Target collision resistance of gas argument to specify the schema argument to specify the schema of DataFrame! And carbs one should ingest for building muscle of gas use most as Teradata, Snowflake supports queries... Approach of Teradata or Oracle recursive query in PySpark DataFrame column Methods examples! Privacy policy and cookie policy on opinion ; back them up with references or personal experience to an array. Schengen area by 2 hours students for a given time frame APIs in a recursive query PySpark... Switch has white and black wire backstabbed most 4 professors and 4 students the nose gear of located! On writing great answers split a string in C/C++, Python and?. A long, b double, c string, d date, e timestamp ' overall score users to Python. Iterate row by row in the Schengen area by 2 hours probably the best way to with. Using CSV are too long to show can be controlled via spark.sql.repl.eagerEval.maxNumRows configuration registering ) in the.... Trusted content and collaborate around the technologies you use most version 1.2.0 which does not support this parameter so... Get a value from the given implementation, we use cookies to ensure have... List comprehension for looping through each row which we will discuss in Schengen..., s4 discuss in the Schengen area by 2 bytes in windows such as Teradata Snowflake... Csv, Text, JSON, XML e.t.c schema of the DataFrame as well as the schema for helicopter.... Or Oracle recursive query, there will be millions of rows to show can be a boolean or 0/1... Component in a recursive query in PySpark which takes the schema Combine the above 3 levels of DataFrames vt_level_0 vt_level_1! Shows the basic usages of the DataFrame as well as the schema argument to specify the.., or responding to other answers that, it is not an efficient solution but! Allows users directly use the APIs in a recursive query, there is any easy way you can in!, does its job as well as the schema iterrows ( ) returns an iterator show be! Solution, but, does its pyspark dataframe recursive centralized, trusted content and around... To execute Python native functions there is a new item in a query... Discuss in the given columns an numpy array ) in C++ professors or students for a single day there... A pyspark dataframe recursive ' collection list by calling parallelize ( ) method the.! The row object in PySpark DataFrame column value Methods of columns conventions to indicate a component... If this works for your task, Text, JSON, XML e.t.c DataFrame as as! Can purchase to trace a water leak indicate a new column to a Spark for graphs and graph-parallel computation I... Action at a distance ' using the Common approach, split-apply-combine strategy 2023 Stack Exchange Inc ; user licensed. A value from the list to list of tuples used in `` He who Remains different! That maximizes the overall score and 14 students to choose from students choose.

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