csv

问题 I have a csv file (image attached) and to take the CSV file and create a dictionary of lists with the format " {method},{number},{orbital_period},{mass},{distance},{year} " . So far I have code : import csv with open('exoplanets.csv') as inputfile : reader = csv.reader(inputfile) inputm = list(reader) print(inputm) but my output is coming out like ['Radial Velocity', '1', '269.3', '7.1', '77.4', '2006'] when I want it to look like : "Radial Velocity" : {"number":[1,1,1], "orbital_period":[269

问题 I know there are many answers but none of them solved my problem. I have a .mat file and i want to export it's data to Csv. The code that i tried: import h5py arrays={} f=h5py.File('datafile.mat') for k,v in f.items(): arrays[k]=np.array(v) Which got me output in dictionary {'#refs#': array(['0', '00', '00b', ..., 'zzj', 'zzk', 'zzl'], dtype='<U3'), 'MasterOperations': array(['Code', 'ID', 'Label'], dtype='<U5'), 'Operations': array(['CodeString', 'ID', 'Keywords', 'MasterID', 'Name'], dtype=

问题 I am new to java and practicing processing csv file. I've already successfully parsed the csv file, saved it in an array, and got rid of the header. The file looks like this: class, gender, age, bodyType, profession, pregnant, species, isPet, role scenario:green, , , , , , , person, female, 24, average , doctor , FALSE , , , passenger animal, male , 4 , , FALSE , dog , true , pedestrian . . the column without a string is empty in the file. Like the species and isPet above. Now, I want to

问题 I am taking over a project with code from another person. I have a PLC that currently has inputs in from pressure sensors and thermocouples. It then scales that data to PSI and temperature in fahrenheit. The way the data is set up from each of those sensors is to be formatted into an array. So, once the data is scaled it is in an array that is also in the Network Variable List of the program. I am trying to take each of these values from the array, record the value every certain amount of

问题 I have a python lambda with nested for loop def lambda_handler(event, context): acc_ids = json.loads(os.environ.get('ACC_ID')) with open('/tmp/newcsv.csv', mode='w', newline='') as csv_file: fieldnames = ['DomainName', 'Subject', 'Status', 'RenewalEligibility', 'InUseBy'] writer = csv.DictWriter(csv_file, fieldnames=fieldnames) writer.writeheader() for acc_id in acc_ids: try: //do something for region in regions_to_scan: try: // do something if something: for x in list: // get values for row

问题 I am trying to first read the CSV file, but I am getting an error saying: TypeError: fs.createReadStream is not a function. Am I doing something wrong? Here is my code: fs.createReadStream('accounts.csv') .pipe(csv()) .on('data', function (data) { console.log(data); }) .on('end', function () { console.log('Read finished'); }); 回答1: I realized that i did not have the file inside my project, which is the reason it was not reading it, also, i changed my code to this. const csv = require('csv

问题 I have a csv of size 6GB. So far I was using the following line which when I check its size on dbfs after this copy using java io, it still shows as 6GB so I assume it was right. But when I do a spark.read.csv(samplePath) it reads only 18mn rows instead of 66mn. Files.copy(Paths.get(_outputFile), Paths.get("/dbfs" + _outputFile)) So I tried dbutils to copy as shown below but it gives error. I have updated maven dbutil dependency and imported the same in this object where I am calling this

问题 I was migrating my code from Spark 2.0 to 2.1 when I stumbled into a problem related to Dataframe saving. Here's the code import org.apache.spark.sql.types._ import org.apache.spark.ml.linalg.VectorUDT val df = spark.createDataFrame(Seq(Tuple1(1))).toDF("values") val toSave = new org.apache.spark.ml.feature.VectorAssembler().setInputCols(Array("values")).transform(df) toSave.write.csv(path) This code succeeds when using Spark 2.0.0 Using Spark 2.1.0.cloudera1, I get the following error : java

问题 I was migrating my code from Spark 2.0 to 2.1 when I stumbled into a problem related to Dataframe saving. Here's the code import org.apache.spark.sql.types._ import org.apache.spark.ml.linalg.VectorUDT val df = spark.createDataFrame(Seq(Tuple1(1))).toDF("values") val toSave = new org.apache.spark.ml.feature.VectorAssembler().setInputCols(Array("values")).transform(df) toSave.write.csv(path) This code succeeds when using Spark 2.0.0 Using Spark 2.1.0.cloudera1, I get the following error : java

问题 I have CSV file which is in the form as below student, year, subject, score1, score2, score3 Alex, 2010, Math, 23, 56, 43 Alex, 2011, Science, 45, 32, 45 Matt, 2009, Art, 34, 56, 75 Matt, 2010, Math, 43, 54, 54 I'm trying to find an optimal solution to read the CSV file and load it to a map for lookup purposes i.e. Map<String, Map<String, List<SubjectScore>>> . The first string key is for student, the next string key is for year. class SubjectScore { private String subject; private int score1