That’s because num is a Char, i.e. the resulting values are the ascii value of that char. This will do the trick: val txt = “82389235” val numbers = txt.map { it.toString().toInt() } The map could be further simplified: map(Character::getNumericValue)
-(NSString*) suffixNumber:(NSNumber*)number { if (!number) return @””; long long num = [number longLongValue]; int s = ( (num < 0) ? -1 : (num > 0) ? 1 : 0 ); NSString* sign = (s == -1 ? @”-” : @”” ); num = llabs(num); if (num < 1000) return [NSString stringWithFormat:@”%@%lld”,sign,num]; int exp = … Read more
Please scroll down for the newer, faster solution This is an older question, but I struggled the entire night to get a satisfactory result for a similar situation, and I came up with this: import json import pandas def cross_join(left, right): return left.assign(key=1).merge(right.assign(key=1), on=’key’, how=’outer’).drop(‘key’, 1) def json_to_dataframe(data_in): def to_frame(data, prev_key=None): if isinstance(data, dict): df … Read more
Do a replace first: parseFloat(str.replace(‘,’,’.’).replace(‘ ‘,”))
ByteBuffer has this capability, and is able to work with both little and big endian integers. Consider this example: // read the file into a byte array File file = new File(“file.bin”); FileInputStream fis = new FileInputStream(file); byte [] arr = new byte[(int)file.length()]; fis.read(arr); // create a byte buffer and wrap the array ByteBuffer bb … Read more
Maybe this might help: JSefa You can read CSV file with this tool and serialize it to XML.
2017-11-20, Completely rewrote function to improve performance and add features as -ArrayBase and support for PSStandardMembers and grouped objects. Flatten-Object Recursively flattens objects containing arrays, hash tables and (custom) objects. All added properties of the supplied objects will be aligned with the rest of the objects. Requires PowerShell version 2 or higher. Cmdlet Function Flatten-Object … Read more
New solution: Built using Your great comments, thanks! SELECT JSON_ARRAYAGG(JSON_OBJECT(‘name’, name, ‘phone’, phone)) from Person; Old solution: With help from @Schwern I managed to put up this query, which seems to work! SELECT CONCAT( ‘[‘, GROUP_CONCAT(JSON_OBJECT(‘name’, name, ‘phone’, phone)), ‘]’ ) FROM person;
import csv to_csv = [ {‘name’: ‘bob’, ‘age’: 25, ‘weight’: 200}, {‘name’: ‘jim’, ‘age’: 31, ‘weight’: 180}, ] keys = to_csv[0].keys() with open(‘people.csv’, ‘w’, newline=””) as output_file: dict_writer = csv.DictWriter(output_file, keys) dict_writer.writeheader() dict_writer.writerows(to_csv)
With java-8, you’ll be able to do this in one line using streams, and the Collectors class. Map<String, Item> map = list.stream().collect(Collectors.toMap(Item::getKey, item -> item)); Short demo: import java.util.Arrays; import java.util.List; import java.util.Map; import java.util.stream.Collectors; public class Test{ public static void main (String [] args){ List<Item> list = IntStream.rangeClosed(1, 4) .mapToObj(Item::new) .collect(Collectors.toList()); //[Item [i=1], Item … Read more