calculated-columns

问题 How do I subtract row 1 from row 2 and row 2 from row 3, etc. in MySQL? The table i am pulling my data from contains multiple products and all products have multiple prices (on different dates) The code i am working with: SELECT orderline_sales.product_name, orderline_sales.price FROM orderline_sales GROUP BY price HAVING orderline_sales.product_name = 'Ibuprofen'; The result I am getting: |---------------------|------------------| | product_name | price | |---------------------|-------------

问题 I have to modify a Dataset<Row> according to some rules that are in a List<Row> . I want to iterate over the Datset<Row> columns using Dataset.withColumn(...) as seen in the next example: (import necesary libraries...) SparkSession spark = SparkSession .builder() .appName("appname") .config("spark.some.config.option", "some-value") .getOrCreate(); Dataset<Row> dfToModify = spark.read().table("TableToModify"); List<Row> ListListWithInfo = new ArrayList<>(Arrays.asList()); ListWithInfo.add(0

问题 I have to convert a column of dates from the integer/date format to the date format d-m-Y. Example: import pandas as pd col1 = [737346, 737346, 737346, 737346, 737059, 737346] col2 = ['cod1', 'cod2', 'cod3', 'cod4', 'cod1', 'cod2'] dict = {'V1' : col1, 'V2' : col2} df = pd.DataFrame.from_dict(dict) df V1 V2 0 737346 cod1 1 737346 cod2 2 737346 cod3 3 737346 cod4 4 737059 cod1 5 737346 cod2 expected: df V1 V2 0 14-10-2019 cod1 1 14-10-2019 cod2 2 14-10-2019 cod3 3 14-10-2019 cod4 4 31-12-2018

问题 Environment: MS SQL Server 2016. I have a table which contains (Jasper Reports) layout representations like this (only relevant fields shown for brevity): ID Name Key Version 1 CoverLetter <guid1> 1.00.00 2 Contract <guid2> 1.00.00 3 CoverLetter <guid1> 1.00.01 Goal: I need an additional calculated field which is set to true or false according to whether the record is the highest version of any given Layout or not (Same layout but different versions have same key, different layouts have

问题 My dataframe look like this Plate Sample LogRatio P1 S1 0.42 P1 S2 0.23 P2 S3 0.41 P3 S4 0.36 P3 S5 0.18 I have calculated the median of each plate (but it's probably not the best idea to start like this) grouped = df.groupby("Plate") medianesPlate = grouped["LogRatio"].median() And I want to add a column on my dataframe CorrectedLogRatio = LogRatio-median(plate) I suppose with : df["CorrectedLogRatio"] = LogRatio-median(plate) To have something like this : Plate Sample LogRatio

问题 Context: I have a data model in Power Pivot with two tables, tTasks and tCaseworks. They are linked through the common field casework_id (unique to tCaseworks). I am attempting to create a calculated column in tCaseworks that checks whether or not that particular casework has any (i.e. one or more) corresponding tasks. I have attempted the following DAX code: has_task = IF ( CONTAINS ( RELATEDTABLE ( tTasks ); tTasks[casework_id]; tCaseworks[casework_id] ); "Yes"; "No" ) Problem: When I have

问题 I have a requirement where I have XML data in database, which I need to pull in the form of row and Column from database. My XML is like <Equipment> <EquipmentRecord> <EquipmentType>E</EquipmentType><MfgName>APPLE iPH564WHT</MfgName><Model>885909600205</Model><ActDate>10/26/2012</ActDate><CancelDate /> </EquipmentRecord> <EquipmentRecord> <EquipmentType>E</EquipmentType><MfgName>SAMSUNG D710 HANDSET KIT</MfgName><Model>SPHD710KIT</Model><ActDate>09/04/2012</ActDate><CancelDate>10/01/2012<

问题 I have a requirement where I have XML data in database, which I need to pull in the form of row and Column from database. My XML is like <Equipment> <EquipmentRecord> <EquipmentType>E</EquipmentType><MfgName>APPLE iPH564WHT</MfgName><Model>885909600205</Model><ActDate>10/26/2012</ActDate><CancelDate /> </EquipmentRecord> <EquipmentRecord> <EquipmentType>E</EquipmentType><MfgName>SAMSUNG D710 HANDSET KIT</MfgName><Model>SPHD710KIT</Model><ActDate>09/04/2012</ActDate><CancelDate>10/01/2012<

问题 I have a requirement where I have XML data in database, which I need to pull in the form of row and Column from database. My XML is like <Equipment> <EquipmentRecord> <EquipmentType>E</EquipmentType><MfgName>APPLE iPH564WHT</MfgName><Model>885909600205</Model><ActDate>10/26/2012</ActDate><CancelDate /> </EquipmentRecord> <EquipmentRecord> <EquipmentType>E</EquipmentType><MfgName>SAMSUNG D710 HANDSET KIT</MfgName><Model>SPHD710KIT</Model><ActDate>09/04/2012</ActDate><CancelDate>10/01/2012<

问题 I am trying to create a new column based on both columns. Say I want to create a new column z, and it should be the value of y when it is not missing and be the value of x when y is indeed missing. So in this case, I expect z to be [1, 8, 10, 8] . x y 0 1 NaN 1 2 8 2 4 10 3 8 NaN 回答1: The new column 'z' get its values from column 'y' using df['z'] = df['y'] . This brings over the missing values so fill them in using fillna using column 'x' . Chain these two actions: >>> df['z'] = df['y']