export-to-csv

问题 I have a list of data frames which I reshuffle and then I want to save the output as a csv. To do this I'm trying to append this list to an empty data frame: l1=[year1, year2,..., year30] shuffle (l1) columns=['year', 'day', 'tmin', 'tmax', 'pcp'] index=np.arange(10957) df2=pd.DataFrame(columns=columns, index=index) l1.append(df2) This result in an empty data frames with a bunch of Nans. I don't necessarily need to append my reshuffled list to a dataframe, I just need to save it as a csv, and

问题 I am using Get-WindowsAutopilotInfo to generate a computer's serial number and a hash code and export that info as a CSV. Here is the code I usually use: new-item "c:\Autopilot_Export" -type directory -force Set-Location "C:\Autopilot_Export" Get-WindowsAutopilotInfo.ps1 -OutputFile Autopilot_CSV.csv Robocopy C:\Autopilot_Export \\Zapp\pc\Hash_Exports /copyall This outputs a CSV file named "Autopilot_CSV.csv" to the C:\Autopilot_Export directory and then Robocopy copies it to the Network

问题 I want to convert my json file into csv - { "count": 28, "value": [ { "commitId": "65bb6a911872c314a9225815007d74a", "author": { "name": "john doe", "email": "john.doe@gmail.com", "date": "2020-06-09T17:03:33Z" }, "committer": { "name": "john doe", "email": "john.doe@gmail.com", "date": "2020-06-09T17:03:33Z" }, "comment": "Merge pull request 3 from dev into master", "changeCounts": { "Add": 6, "Edit": 0, "Delete": 0 }, "url": "https://dev.azure.com/", "remoteUrl": "https://dev.azure.com/" },

问题 I am using pandas to normalize some json data. I am getting stuck on this issue when more than 1 section is either an object or an array. If i use the record_path on Car it breaks on the second. Any pointers on how to get something like this to create a line in the csv per Car and per Location? [ { "Name": "John Doe", "Car": [ "Car1", "Car2" ], "Location": "Texas" }, { "Name": "Jane Roe", "Car": "Car1", "Location": [ "Illinois", "Kansas" ] } ] Here is the output Name,Car,Location John Doe,"[

问题 I am using pandas to normalize some json data. I am getting stuck on this issue when more than 1 section is either an object or an array. If i use the record_path on Car it breaks on the second. Any pointers on how to get something like this to create a line in the csv per Car and per Location? [ { "Name": "John Doe", "Car": [ "Car1", "Car2" ], "Location": "Texas" }, { "Name": "Jane Roe", "Car": "Car1", "Location": [ "Illinois", "Kansas" ] } ] Here is the output Name,Car,Location John Doe,"[

问题 Here is the summary of what I'm doing: At first, I do this by normal multiprocessing and pandas package: Step 1. Get the list of files name which I'm gonna to read import os files = os.listdir(DATA_PATH + product) Step 2. loop over the list from multiprocessing import Pool import pandas as pd def readAndWriteCsvFiles(file): ### Step 2.1 read csv file into dataframe data = pd.read_csv(DATA_PATH + product + "/" + file, parse_dates=True, infer_datetime_format=False) ### Step 2.2 do some

问题 Here is the summary of what I'm doing: At first, I do this by normal multiprocessing and pandas package: Step 1. Get the list of files name which I'm gonna to read import os files = os.listdir(DATA_PATH + product) Step 2. loop over the list from multiprocessing import Pool import pandas as pd def readAndWriteCsvFiles(file): ### Step 2.1 read csv file into dataframe data = pd.read_csv(DATA_PATH + product + "/" + file, parse_dates=True, infer_datetime_format=False) ### Step 2.2 do some

问题 Here is the summary of what I'm doing: At first, I do this by normal multiprocessing and pandas package: Step 1. Get the list of files name which I'm gonna to read import os files = os.listdir(DATA_PATH + product) Step 2. loop over the list from multiprocessing import Pool import pandas as pd def readAndWriteCsvFiles(file): ### Step 2.1 read csv file into dataframe data = pd.read_csv(DATA_PATH + product + "/" + file, parse_dates=True, infer_datetime_format=False) ### Step 2.2 do some

问题 Here is the summary of what I'm doing: At first, I do this by normal multiprocessing and pandas package: Step 1. Get the list of files name which I'm gonna to read import os files = os.listdir(DATA_PATH + product) Step 2. loop over the list from multiprocessing import Pool import pandas as pd def readAndWriteCsvFiles(file): ### Step 2.1 read csv file into dataframe data = pd.read_csv(DATA_PATH + product + "/" + file, parse_dates=True, infer_datetime_format=False) ### Step 2.2 do some

问题 I've adopted some code which converts a DataTable into a CSV file. It seems to work well, except for when commas are used in the actual data. Is there a way to display the comma in that case? This is what I've done: StringBuilder sb = new StringBuilder(); IEnumerable<string> columnNames = dtResults.Columns .Cast<DataColumn>() .Select(column => column.ColumnName); sb.AppendLine(string.Join(",", columnNames)); foreach (DataRow row in dtResults.Rows) { IEnumerable<string> fields = row.ItemArray