csv

问题 I'm trying to read a large and complex CSV file with pandas.read_csv. The exact command is pd.read_csv(filename, quotechar='"', low_memory=True, dtype=data_types, usecols= columns, true_values=['T'], false_values=['F']) I am pretty sure that the data types are correct. I can read the first 16 million lines (setting nrows=16000000) without problems but somewhere after this I get the following error ValueError: could not convert string to float: '1,123' As it seems, for some reason pandas

问题 I want to calculate the average for each hours using a CSV file: Below is my DATA SET: Timestamp Temperature 9/1/2016 0:00:08 53.8 9/1/2016 0:00:38 53.8 9/1/2016 0:01:08 53.8 9/1/2016 0:01:38 53.8 9/1/2016 0:02:08 53.8 9/1/2016 0:02:38 54.1 9/1/2016 0:03:08 54.1 9/1/2016 0:03:38 54.1 9/1/2016 0:04:38 54 9/1/2016 0:05:38 54 9/1/2016 0:06:08 54 9/1/2016 0:06:38 54 9/1/2016 0:07:08 54 9/1/2016 0:07:38 54 9/1/2016 0:08:08 54.1 9/1/2016 0:08:38 54.1 9/1/2016 0:09:38 54.1 9/1/2016 0:10:32 54 9/1

问题 I want to calculate the average for each hours using a CSV file: Below is my DATA SET: Timestamp Temperature 9/1/2016 0:00:08 53.8 9/1/2016 0:00:38 53.8 9/1/2016 0:01:08 53.8 9/1/2016 0:01:38 53.8 9/1/2016 0:02:08 53.8 9/1/2016 0:02:38 54.1 9/1/2016 0:03:08 54.1 9/1/2016 0:03:38 54.1 9/1/2016 0:04:38 54 9/1/2016 0:05:38 54 9/1/2016 0:06:08 54 9/1/2016 0:06:38 54 9/1/2016 0:07:08 54 9/1/2016 0:07:38 54 9/1/2016 0:08:08 54.1 9/1/2016 0:08:38 54.1 9/1/2016 0:09:38 54.1 9/1/2016 0:10:32 54 9/1

问题 I want to calculate the average for each hours using a CSV file: Below is my DATA SET: Timestamp Temperature 9/1/2016 0:00:08 53.8 9/1/2016 0:00:38 53.8 9/1/2016 0:01:08 53.8 9/1/2016 0:01:38 53.8 9/1/2016 0:02:08 53.8 9/1/2016 0:02:38 54.1 9/1/2016 0:03:08 54.1 9/1/2016 0:03:38 54.1 9/1/2016 0:04:38 54 9/1/2016 0:05:38 54 9/1/2016 0:06:08 54 9/1/2016 0:06:38 54 9/1/2016 0:07:08 54 9/1/2016 0:07:38 54 9/1/2016 0:08:08 54.1 9/1/2016 0:08:38 54.1 9/1/2016 0:09:38 54.1 9/1/2016 0:10:32 54 9/1

问题 I'm using Jmeter v 4.0 r1823414 . According to this answer, there is an advisory to use JSR223 PostProcessor, verbatim: it is recommended to use Groovy for any form of scripting to consider migrating to JSR223 PostProcessor Before this approach I tried to use BeanShell Sampler to simply write data to csv file. The code sample I took from the blazemeter tutorial page. However, I was getting error Sourced file: inline evaluation of: ``import java.io.FileWriter; import java.util.Arrays; import

问题 This question already has answers here : How to determine the delimiter in CSV file (5 answers) Closed 1 year ago . I saw that this question was already asked several times but they're on other language and I can't get a grasp on the answers. I am receiving a .csv or .txt file through a socket. Is there any way I can detect the delimiter or "splitter" of a line in the CSV or TXT file? This is the server code that handles the file writing, try{ final ServerSocket server = new ServerSocket(8998

问题 "INSERT INTO CricketMatch (FName,LastName,Runs,Matches,Location,DateofMatch,PLayerId) SELECT Fname,Lname,Runsby,numberofMatches,MatchLocation,DofMatch,Id FROM [Text;Data Source=C:\\DB\\;HDR=YES].[filename]"; filename is just name with extension demo.csv no path cmd.CDataSet da = new DataSet();string filename = Path.GetFileName(txtCSVFilePath.Text); try {da = this.ConnectCSV(filename); string connstring = "Provider=Microsoft.ACE.OLEDB.12.0;Data Source=C:\\DB\\MatchDetails.accdb";

问题 "INSERT INTO CricketMatch (FName,LastName,Runs,Matches,Location,DateofMatch,PLayerId) SELECT Fname,Lname,Runsby,numberofMatches,MatchLocation,DofMatch,Id FROM [Text;Data Source=C:\\DB\\;HDR=YES].[filename]"; filename is just name with extension demo.csv no path cmd.CDataSet da = new DataSet();string filename = Path.GetFileName(txtCSVFilePath.Text); try {da = this.ConnectCSV(filename); string connstring = "Provider=Microsoft.ACE.OLEDB.12.0;Data Source=C:\\DB\\MatchDetails.accdb";

问题 Below is a working code to connect to a SQL server,and save 1 table to a CSV format file. conf = new SparkConf().setAppName("test").setMaster("local").set("spark.driver.allowMultipleContexts", "true"); sc = new SparkContext(conf) sqlContext = new SQLContext(sc) df = sqlContext.read.format("jdbc").option("url","jdbc:sqlserver://DBServer:PORT").option("databaseName","xxx").option("driver","com.microsoft.sqlserver.jdbc.SQLServerDriver").option("dbtable","xxx").option("user","xxx").option(

问题 I've seen a few answers on reading multiple csv files into separate Pandas dataframes, and am still running into trouble. I've read my csv files and file names into a dictionary: path = os.getcwd() file_names = ['file1', 'thisisanotherfile', 'file3'] df_dict = {x: pd.read_csv('{}/{}.csv'.format(path, x)) for x in file_names} Which seems to work: print(df_dict['file1']) However what I'm looking for is a Pandas dataframe called 'file1' where I can access the data. Is it possible to get this