You can try the some thing like the below LINQ snippet. string[] allLines = File.ReadAllLines(@”E:\Temp\data.csv”); var query = from line in allLines let data = line.Split(‘,’) select new { Device = data[0], SignalStrength = data[1], Location = data[2], Time = data[3], Age = Convert.ToInt16(data[4]) }; UPDATE: Over a period of time, things evolved. As of … Read more
import pandas as pd pd.read_csv(“your_file.txt”, engine=”python”) Try this. It totally worked for me. source : http://kkckc.tistory.com/187
Use a category when there is lots of repetition that you expect to exploit. For example, suppose I want the aggregate size per exchange for a large table of trades. Using the default object is totally reasonable: In [6]: %timeit trades.groupby(‘exch’)[‘size’].sum() 1000 loops, best of 3: 1.25 ms per loop But since the list of … Read more
You can use the tilde ~ to flip the bool values: >>> df = pd.DataFrame({“A”: [“Hello”, “this”, “World”, “apple”]}) >>> df.A.str.contains(“Hello|World”) 0 True 1 False 2 True 3 False Name: A, dtype: bool >>> ~df.A.str.contains(“Hello|World”) 0 False 1 True 2 False 3 True Name: A, dtype: bool >>> df[~df.A.str.contains(“Hello|World”)] A 1 this 3 apple [2 … Read more
You need to call join() on the tags list, not the individual tags. Try with: jq -r ‘.tickets[] | [.created_at, .id, .via.channel, (.tags | join(“,”))] | @csv’
The File API suggested by papaparse’s docs is meant for browser used. Assuming that you are running this on node at server side, what works for me is leveraging the readable stream: const fs = require(‘fs’); const papa = require(‘papaparse’); const file = fs.createReadStream(‘challenge.csv’); var count = 0; // cache the running count papa.parse(file, { … Read more