Pandas aggregate conditional. Parameters: func function, str, list or dict.

Pandas aggregate conditional Previous Pandas agg Next Pandas agg List. Agg# class seaborn. Viewed 853 times Jan 30, 2015 · Suppose I have a dataframe like so: a b 1 5 1 7 2 3 1 3 2 5 I want to sum up the values for b where a = 1, for example. Check your Pandas version by running print(pd. The problem is that the first aggregation will transform condition condition_B_cluster and condition_C_cluster into "list" or clusters which starts to complicate things. aggregate under certain condition. df = df. Is there any elegant way to do this in python ? Conditional Pandas Groupby lets you efficiently filter and group data based on specified conditions. loc# property DataFrame. 0 1 toy 2 5 200. sum ()). groupby(' some_column '). 0. You can use pandas groupby with condition to aggregate data by calculating the mean, sum, standard deviation, and other statistics for each group. 0 7. fillna(df['b']) print (df) condition a b total name one 7. The most frequently used aggregations are: Jun 10, 2022 · You can use the following methods to count the number of values in a pandas DataFrame column with a specific condition: Method 1: Count Values in One Column with Condition len(df[df[' col1 ']==' value1 ']) You can read on Pandas logical operators and conditional selection here: Logical operators for boolean indexing in Pandas. Feb 19, 2024 · The DataFrame. Jun 14, 2021 · I want to aggregate these two rows into one. Sep 11, 2017 · Python Pandas: Aggregate rows conditional value picking. DF Jul 20, 2019 · Multiple aggregations of the same column using pandas GroupBy. values] print(res) Balance_mean Balance_sum ATM_drawings_mean ATM_drawings_sum ID 1 125 250 41. If 0 or ‘index’: apply function to each column. Here is my df: Sep 29, 2021 · Stack Overflow for Teams Where developers & technologists share private knowledge with coworkers; Advertising & Talent Reach devs & technologists worldwide about your product, service or employer brand Feb 1, 2024 · To count values that meet a condition in any row or column of a DataFrame, specify the row or column using [], loc[], iloc[], and perform the same process. One of the key functionalities provided by Pandas is the . loc[d. transform(func) df. Accepted Jan 18, 2024 · In pandas, you can apply multiple operations to rows or columns in a DataFrame and aggregate them using the agg() and aggregate() methods. agg (func = None, axis = 0, * args, ** kwargs) [source] # Aggregate using one or more operations over the specified axis. 3 documentation; pandas. Aug 2, 2018 · You can use a dictionary to specify aggregation functions for each series: d = {'Balance': ['mean', 'sum'], 'ATM_drawings': ['mean', 'sum']} res = df. Pandas聚合函数中的条件求和操作 在本文中，我们将介绍如何在Pandas聚合函数中使用条件求和操作。在实际工作中，我们通常需要对数据进行统计和分析，而条件求和操作可以帮助我们更快捷、高效地完成这些任务。 Dec 11, 2024 · Key Points – The groupby() function allows you to group data based on multiple columns by passing a list of column names. 0 5 Kerala 12. 0 1 book 3 6 200. 25 docs section on Enhancements as well as relevant GitHub issues GH18366 and GH26512. Can this be done elegantly without using . Accepted combinations are: dict of axis labels -> functions, function names or list of such. A counted 847 2. groupby(['Sp', 'Mt'])['count']. groupby(['type', 'status', 'name']). This tutorial assumes that you have some experience with pandas itself, including how to read CSV files into memory as pandas objects with read_csv(). 0 2 car 0 1 20. First, you can create a conditional mask based on your criteria and then use this mask to group your data. 23 2 2017-02-01 01:00:00 01/01/2017 Jan Sun 01:00 60 Mar 3, 2022 · I need to perform some aggregations on a pandas dataframe. 5 pandas is a fast, powerful, flexible and easy to use open source data analysis and manipulation tool, built on top of the Python programming language. reset_index () This particular example example calculates the mean value of points , grouped by position , where team is equal to ‘A’ in some pandas DataFrame. This seems a scary operation for the dataframe to undergo, so let us first split the I would like to use Panda's groupby with multiple aggregation functions, but also including conditional statements per aggregation. Dec 4, 2023 · pandas. Index Name Item Quantity 0 John Apple Red 10 1 John Apple Green 5 2 John Orange Cali 12 3 Jane Apple Red 10 4 Jane Apple Green 5 5 Jane Orange Cali 18 6 Jane Orange Spain 2 7 John Banana 3 8 Jane Coconut 5 9 John Lime 10 Dec 24, 2018 · If you want to create a Function: def my_agg(x): names = { 'Total_Count': x['Type']. pandas group by aggregate dataframe by condition of 2 columns. Nov 7, 2019 · Groupby aggregate based on multiple condition pandas. A estimated 4874 1. Name of a pandas. Pandas provides the pandas. Whether using preset functions, lists of functions, or custom ones, agg() can address a wide range of data summarization needs. count(). Thanks. ) This was the second episode of my pandas tutorial series. May 21, 2018 · Pandas groupby and agg by condition. Parameters: func function, str, list, dict or None. groupby (' var1 ')[' var2 ']. The examples provided showcase just a fraction of what’s possible, encouraging exploration Mar 12, 2024 · Pandas is one of those packages and makes importing and analyzing data much easier. To make a custom aggregation function, all we need to do is create a function that intakes a Series (or list) and returns a single number. Feb 19, 2024 · Introduction. groupby(['category'])['ID']. . Oct 29, 2021 · I want to aggregate time-series data based on several conditions. I want to add a condition such that it takes sum only when is_b is 1. aggregate() function is used to apply some aggregation across one or more columns. max() Out[2]: Sp Mt MM1 S1 3 S3 5 MM2 S3 8 S4 10 MM4 S2 7 Name: count, dtype: int64 Sep 8, 2016 · You could use DFGroupby. Pandas is an open-source library that is built over Numpy libraries. Parameters: func function, str, list or dict. Current code: clean_df = clean_df. objects. A few of the aggregate functions are average, count, maximum, among others. __version__). Dec 12, 2022 · In Pandas DataFrames, applying conditional logic to filter or modify data is a common task. See the 0. Let's explore different ways to apply an 'if condition' in Pandas DataFrame. 0 1 computer 1 3 100. Modified 4 years, 3 months ago. Apart of grouping the data by a timespan and the "type"- column, I would like to count and sum only positive values in the respective groups. 0 48. We normally use lambda functions to apply any condition on a dataframe, Jan 15, 2022 · 它是为了支持特定于列的聚合并控制输出列名，pandas 接受 GroupBy 中的特殊语法。它是 agg() 的“命名聚合”，其中关键字是输出列名（NamedAgg 位），值是元组，其第一个元素（column 位）是要选择的列，第二个元素（aggfunc 位）是要应用于该列的聚合。 pandas. pandas. The values are tuples whose first element is the column to select and the second element is the aggregation to apply to that column. unstack() df['total'] = df['a']. If either of them is positive, the result will be greater than 1. 3. Now you see that aggregation and grouping are not too hard in pandas… and believe me, you will use them a lot! Note: If you have used SQL before, I encourage you to take a break and compare the pandas and the SQL methods of Dec 20, 2021 · The Pandas groupby method is an incredibly powerful tool to help you gain effective and impactful insight into your dataset. DataFrame. I like this approach as it's quite robust - another answer outlines a very elegant approach using crosstab but I wonder how extensible that would be. This allows you to appl Dec 10, 2024 · Combining multiple columns in Pandas groupby operation with a dictionary helps to aggregate and summarize the data in a custom manner. agg({ 'rq_id':'first', 'method':"". index, 'x'][d >= -0. Series method or a vector -> scalar function. 2. Apr 20, 2022 · In this article, we are going to see how to apply multiple if statements with lambda function in a pandas dataframe. Learn how to use the `pandas. 0 39. Mar 6, 2023 · I want to aggregate DataFrame based on a condition and I am able to do it but not for every scenario, here is an example: import pandas as pd import numpy as np th=0. 5 6 Punjab 15. transform() methods with examples. 3. NamedAgg namedtuple with the fields ['column', 'aggfunc'] to make it clearer what the arguments are. When analyzing data with Python, Pandas is one of the go-to libraries thanks to its powerful and easy-to-use data structures. Helper for column specific aggregation with control over output column names. Jul 2, 2018 · You can aggregate groupby with aggregate sum and reshape by unstack, last replace NaNs for missing catagories a by fillna:. 0 3 Haryana 7. It seems I am only able to use builtin python functions, such as the max function, to aggregate columns that Aug 20, 2020 · There are several functions in pandas that proves to be a great help for a programmer one of them is an aggregate function. price. EDIT. groupby() provides a function to split the dataframe, apply a function such as mean() and sum() to form the grouped dataset. 0 1 Kerala 2. 3 documentation Dec 23, 2020 · Expanding on the question here, I'm wondering how to add aggregation to the following based on conditions:. Conditional aggregation in python/pandas. Note: Passing a dict to groupby/agg has been Aug 13, 2013 · Here's a solution which has the following benefits: You don't need to define a function in advance; You can use it within a pipe (since it's using lambda) Dec 14, 2018 · 1. agg in favour of a more intuitive syntax for specifying named aggregations. See the example below: Say I want to sum the "Number_mentions" column for each value in the "Newspaper" column if the value of "Number_mentions" is above a threshold. Pandas >= 0. pythonic conditional aggregation. NamedAgg (column, aggfunc) [source] #. groupby('rq_id'). Groupby() is a powerful function in pandas that allows you to group data based on a single column or more. diff(). Viewed 366 times Oct 8, 2020 · 파이썬 버전 3. Solution #1: We can use simple indexing operation to select all those values in the column which satisfies the given condition. is_b is another column where there are 2 values 0 and 1. join, 'user_id':'first', # <=== here what do I do? Apr 9, 2024 · df. loc[] is primarily label based, but may also be used with a boolean array. 테이블형태로 정리해주는 함수 어플리케이션: pipe() 행 혹은 열로 정리해주는 As an experienced Python developer and teacher for over 15 years, I often get asked about using Pandas groupby for data analysis. In particular, GroupBy objects have aggregate(), filter(), transform(), and apply() methods that efficiently implement a variety of useful operations before combining the grouped data. One option here would be to use a groupby. columns = ['_'. If a function, must either work when passed a DataFrame or when passed to DataFrame. format(comparison)) So, for example, if you want all rows in above the median B-value in each A-group you call I want to aggregate one column with a pandas pivot table, but the custom aggregation should be conditional on a different column in the dataframe. – Nov 9, 2020 · In other instances, this activity might be the first step in a more complex data science analysis. This can be done by using nested if-else statements within the lambda function. 8 기준pandas 버전 1. By the end of this tutorial, you’ll have learned the 3 days ago · Hope you like the article and know you have clear understanding of the topics, pandas groupby aggregate, group by in pandas, groupby aggregate pandas. The groupby method is immensely powerful for splitting dataset into groups, applying aggregate functions, and deriving insights. agg()), which allows for applying one or more operations to DataFrame columns. assign(group = lambda df: df. 0 13. Key Takeaways. A estimated 1152 3. Pandas is a special tool that allows us to perform complex manipulations of data effectively and efficiently. Mar 6, 2021 · In this article, we will learn how to make such complex grouping commands in pandas. To perform row-wise COUNTIF/SUMIF, you can use axis=1 argument. Subclass of typing. 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. sum(). Dataframe. apply. Pandas offer various operations and data structures to perform numerical data manipulations and time series. 5 4 Delhi 10. Improve this answer. Parameters: func str or callable. This is a powerful technique for data analysis and manipulation in Python. 'value'), then the keys in dict passed to agg are taken to be the column names. apply ( lambda x: (x==' val '). Whether you are performing simple or advanced data aggregations, lambda functions can help streamline your data processing workflows in Pandas. groupby ([" position "])[" points "]. Sep 17, 2023 · The Pandas groupby method is a powerful tool that allows you to aggregate data using a simple syntax, while abstracting away complex calculations. Pandas df. I have a CSV file that contains 3 columns, the State, the Office ID, and the Sales for that office. States Sales 0 Delhi 0. agg# DataFrame. This is incredibly useful for data analysis, allowing you to isolate specific subsets of your data and perform calculations on those subsets. DataFrameGroupBy. As usual, the aggregation can be a callable or a string alias. Groupby aggregate based on multiple condition pandas. Aggregation on other hand operates on ser Aug 1, 2023 · Sequentially, by grouping first by condition_A_cluster, then condition_B_cluster and finally by condition_C_cluster. filter(lambda x: some condition) By using this syntax, you can group the rows of a pandas DataFrame by one or more specific columns, then filter the grouped rows to only show the “groups” that meet a particular condition. Dec 15, 2014 · def get_group_rows(df, group_col, condition_col, func=max, comparison='=='): g = df. core. 25 or above then the following code will work: Nov 28, 2022 · Aggregate Pandas DataFrame based on condition that uses multiple columns? 1. agg(d) # flatten MultiIndex columns res. Imagine having this data as an example: df = pd. 0 3 door 3 Jun 3, 2024 · You can conditionally aggregate a pandas DataFrame by using the groupby function along with transform and agg methods. Function to use for aggregating the data. pandas: Select rows/columns by index (numbers and names) Nov 5, 2024 · In this article, you have learned how to group single and multiple columns and get the row counts for each group from Pandas DataFrame using df. NamedAgg# class pandas. agg like you have done before followed by writing a generic function which computes the necessary requirements with the help of str. Problem I have is with the user_id column, because in some of the rows it exists only in one of the rq_id, but some of the rows it exists in both. sort_values('price') . Ask Question Asked 4 years, 3 months ago. groupby(['name','condition'], sort=False)['data1']. 25. Jan 9, 2019 · I am trying to aggregate the total sum of weights for a particular date. Allow me to explain. 1 기준 다수의 함수 사용을 위한 agg() pandas의 객체에 다른 라이브러리의 함수를 적용하는 방법이 존재한다. 23 1 2017-01-03 00:00:00 01/01/2017 Jan Sun 00:00 60. groupby() method Nov 17, 2022 · Learn, how to find the conditional sum for a groupby object? Submitted by Pranit Sharma, on November 17, 2022 . Groupby() is a function used to split the data in dataframe into groups based on a given condition. Nov 22, 2024 · To combine sum and conditional count in pandas, you can use the groupby function to group the data based on a specific condition, and then apply the agg function to calculate the sum and count for each group. Also for COUNTIF (similar to the pandas equivalent of COUNTIFS), it suffices to sum over the condition while for SUMIF, we need to index the frame. 0 2 apple 0 0 22. Again, the range is given as a list of columns (['A', 'B']) similar to how range is fed to COUNTIF. Access a group of rows and columns by label(s) or a boolean array. sum(), 'Count_Status=Y': x[x['Status']=='Y Sep 2, 2017 · I am currently doing this through adding a conditional column and then summing it along with 'value' in pivot and then dividing, but my database is huge (1gb+) and there has got to be an easier way. Sep 22, 2018 · @MarcoBonelli I did try the approaches by more than 2 passes. sum(), . 0 two NaN 48. If your Pandas version is 0. filter or creating subsets beforehand, and merging the aggregate data after? data = data. I want to apply two different aggregates on the same column in a pandas DataFrameGroupBy and have the new columns be named. It can be used to filter data. #changed timestamp values only for better sample print (df) timestamp date month day hour price 0 2017-01-01 00:00:00 01/01/2017 Jan Sun 00:00 60. pandas has quite a lot of different ways to aggregate information. This would give me 5 + 7 + 3 = 15. gt(2). g. Aggregating With Row Reduction Similar to SQL Group By 1. agg() is an alias for aggregate(), and both return the same r An easy way to group that is to use the sum of those two columns. I'm using pandas version 1. Pandas library is known for its high pro Sep 27, 2021 · I am trying to calculate aggregate using a lambda function with if else. For example, you can use the following code to calculate the total sum and count for each group based on a condition: pandas. NamedTuple. 0 1 banana 0 4 27. How do I do this in pandas? Jun 25, 2021 · This builds off @Panwen Wang's solution, and sticking with Pandas: Get the contiguous rows via cumsum and diff : temp = (df . Here are some of the benefits of using pandas groupby with condition: It can be used to aggregate data. By the end of this tutorial, you’ll have learned how the Pandas . I want to calculate the percent Firstly, we can get the max count for each group like this: In [1]: df Out[1]: Sp Mt Value 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 dgd 1 6 MM4 S2 rd 2 7 MM4 S2 cb 2 8 MM4 S2 uyi 7 In [2]: df. In just a few, easy to understand lines of code, you can aggregate your data in incredibly straightforward and powerful ways. aggregate (func = None, axis = 0, * args, ** kwargs) [source] # Aggregate using one or more operations over the specified axis. aggregate (func = None, * args, engine = None, engine_kwargs = None, ** kwargs) [source] # Aggregate using one or more operations over the specified axis. Edit: Expected Output abc 16. agg() (5 answers) Closed 5 years ago . aggregate# DataFrame. agg({'x': lambda d: df. reset_index (name=' count ') Aggregate using one or more operations over the specified axis. groupby() Pandas df. mean(), and . DataFrame({'ID1':['A','A','A','A','A','A','B','B','B','B'], 'ID2':['a','a','a','aa','aaa','aaa','b','b','bb','bb'], Feb 10, 2020 · My data frame looks "like" this: index name method values 0. May 23, 2024 · Pandas is a great python package for manipulating data and some of the tools which we learn as a beginner are an aggregation and group by functions of pandas. One of the strongest benefits of the groupby method is the ability to group by multiple columns, and even apply multiple transformations. The KeyErrors are Pandas' way of telling you that it can't find columns named one, two or test2 in the DataFrame data. 25: Named Aggregation Pandas has changed the behavior of GroupBy. ; You can apply aggregation functions (like sum, mean, count) to groups defined by multiple columns, making it easier to analyze data at multiple levels of granularity. B estimat This is obviously simple, but as a numpy newbe I'm getting stuck. Sep 22, 2016 · but I want to add there condition connected with df. Sep 22, 2015 · This is because in pandas when you compare a series against a scalar value, it returns the result of comparing each row of that series against the scalar value and the result is a series of True/False values indicating the result of comparison of that row with the scalar value. However, certain columns depend on a flag. agg — pandas 2. sum()}) Jun 18, 2022 · Conclusion (pandas groupby, count, sum, min, max, etc. 1. 아래의 메서드는 다른 라이브러리의 함수를 적용하는데 사용되는 메서드들이다. You can then use the agg method to aggregate your data based on your desired function, such as sum, mean, count, etc. Can anyone advise as to how to use the condition with groupby in pandas. You can use custom functions with pandas . It is useful when you want to apply different aggregation functions to different columns of the same dataset. Groupby aggregation in pandas and specific condition. 6]. Ask Question Asked 7 years, 6 months ago. aggregate() method (or its alias . 0 200 Oct 28, 2024 · Python Pandas- Apply Lambda Multiple Conditions. Converted to my code this would be: res2 = g. C/C++ Code # importing pandas as pd import pandas as pd # Cre seaborn. My dataframe looks like this. count() and if count for category less than 5 , I want to drop this category. Python Pandas aggregation with condition. join(col) for col in res. In this comprehensive guide, you‘ll learn: What is […] Jun 9, 2020 · Before I start, I want to make it clear that my question is different than Counting values that meet a condition and Want to count the number of values in a column that meet a condition. 67 (since abc and E is 1 out of total abc which is 6) def 77. startswith and returns the required frame as shown: Aggregate Pandas DataFrame based on condition that uses multiple columns? 1. I wanted pandas function to be able to do this in single pass. count(), 'Total_Number': x['Number']. cumsum()) ) temp price weight product group 2 18. DataFrame, Seriesのagg()およびaggregate()メソッドを使うと、行・列に一度に複数の処理を適用して集約できる。agg()はaggregate()のエイリアスで、どちらを使っても同じ。 pandas. This can be useful for summarizing data or identifying trends. 0 7 Haryana 17. Sometimes in the real world, we will need to apply more than one conditional statement to a dataframe to prepare the data for better analysis. groupby()` function with a `where` condition to filter your data and perform aggregate operations on groups of rows. Share. In pandas, the groupby function can be combined with one or more aggregation functions to quickly and easily summarize data. agg() If you don't mention the column (e. 5 3 mouse 3 7 202. Accepted Jan 19, 2025 · Common aggregation methods in pandas include . Solution use GroupBy. groupby(), size(), count() and DataFrame. You can use Lambda functions in Pandas to apply conditional logic to data. For example, the following Lambda if-else Pandas function checks if a value is less than 1000000 and returns "Small" if it is or "Large" if it Jan 27, 2025 · Pandas in Python is a package that is written for data analysis and manipulation. Grouping in Pandas using df. query (" team == 'A' "). 1. Jan 21, 2023 · The idea is: I want to group by name, and aggregate all the columns. 5 tuples = list(zip(*[ Aggregate, filter, transform, apply¶ The preceding discussion focused on aggregation for the combine operation, but there are more options available. Learn 5 different ways to apply an IF condition in Pandas DataFrame. That is the reason it was specified that i want it using pandas apply agg. Aggregate using callable, string, dict, or list of string/callables. This concept is deceptively simple and most new pandas users will understand this concept. groupby. 78 (since def and E is 7 out of total def of 9); Jan 25, 2018 · If want filter data by conditions use boolean indexing with boolean mask created by compare dayofweek with isin for check membership in list L:. Pandas groupby() transform; Pandas groupby() aggregate explained; Pandas groupby() sort Jan 27, 2022 · I have a dataframe like this: df_test = pd. one creating arrays of >0 vals and <0 and running mean on the same. aggregate# DataFrameGroupBy. I have the following dataframe: key1 key2 0 a one 1 a two 2 b one 3 b two 4 a one 5 c two Now, I want to group the dataframe by the key1 and count the column key2 with the value "one" to get this result: Jun 24, 2013 · I'm looking for the Pandas equivalent of the following SQL: SELECT Key1, SUM(CASE WHEN Key2 = 'one' then data1 else 0 end) FROM df GROUP BY key1 FYI - I've seen conditional sums for pandas aggregate but couldn't transform the answer provided there to work with sums rather than counts. 0 Jun 2, 2016 · There is a related question at how to get multiple conditional operations after a Pandas groupby? which, however, only "filters" by row values not by the number of group elements. query('condition_col {} @condition_limit'. Series. 5 2 Punjab 5. agg() method in Pandas offers a flexible way to aggregate data across different dimensions of your DataFrame. Aug 1, 2018 · You cannot use agg, because each function working only with one column, so this kind of filtering based of another col is not possible. columns. Using apply() with a Lambda FunctionWe can apply an "if condition" by using apply() with a lambda function. Happy Learning !! Related Articles. In this case, sales will be aggregated no matter what, but profit should be included in the aggregation only if profit_flag is True . 1 If Pandas version >=0. Modified 7 years, 6 months ago. Oct 19, 2023 · “Group by with condition” refers to using the “GROUP BY” clause with a conditional filter to aggregate and summarize data based on import pandas as pd df=hotel_reviews df_c Jun 7, 2021 · Aggregate Pandas DataFrame based on condition that uses multiple columns? 1. Nov 21, 2018 · I need to group a dataframe, but I need to create two columns, one that is a simple count and another that is a count with conditional, as in the example: The qtd_ok column counts only those that h Dec 1, 2022 · The easiest way to use group by with a where condition in pandas is to use the query() function: df. loc [source] #. Mastering it is key for effective data manipulation. Jan 7, 2022 · In this post, we will learn how to filter column values in a pandas group by and apply conditional aggregations such as sum, count, average etc. This function returns a single value from multiple values taken as input which are grouped together on certain criteria. Agg (func = 'mean') # Aggregate data along the value axis using given method. groupby() to perform specific operations on groups. Aug 7, 2024 · Given a Dataframe, return all those index labels for which some condition is satisfied over a specific column. 0 three 39. Aggregate Pandas DataFrame with condition using NamedAgg. Jan 20, 2021 · In addition to using the default aggregation functions provided in pandas/numpy, we can also create out own aggregation functions and call them using agg. 5 83 2 100 200 100. apply: Jun 10, 2022 · You can use the following basic syntax to perform a groupby and count with condition in a pandas DataFrame: df. groupby(group_col)[condition_col] condition_limit = g. 0 3. DataFrame({ May 23, 2024 · Pandas is a great python package for manipulating data and some of the tools which we learn as a beginner are an aggregation and group by functions of pandas. mean (). They allow for inline function definition, which can make your code more concise and readable, especially when dealing with complex aggregation logic. groupby('ID'). ehit mebulv cfihnhx vlgc ley ncaz wrys ntqjych nauzpcy cqi jjcteelt xlmeb jllrq ljpc rlxpj