kconner

macOS Internals

Understand your Mac and iPhone more deeply by tracing the evolution of Mac OS X from prelease to Swift. John Siracusa delivers the details.

Starting Points

How to use this gist

You've got two main options:

grcatlin

library(XML)
library(data.table)
library(lubridate)
library(ggplot2)
library(stringr)
library(leaflet)

# import and divide xml file ----------------------------------------------

# import

yuenhsu

import xmltodict
import json
import numpy as np
import pandas as pd

#Parse XML to dictionary
with open('export.xml') as f:
    health = xmltodict.parse(f.read())

#Extract desired data and turn into a Data Frame

andrewrk

int main(int argc, char **argv) {
    struct SoundIo *soundio = soundio_create();
    if (!soundio) {
        fprintf(stderr, "out of memory\n");
        return 1;
    }
    int err;
    if ((err = soundio_connect(soundio))) {
        fprintf(stderr, "unable to connect: %s\n", soundio_strerror(err));
        soundio_destroy(soundio);

ryanpraski

library(dplyr)
library(ggplot2)
library(lubridate)
library(XML)

#load apple health export.xml file
xml <- xmlParse("C:\\Users\\praskry\\Desktop\\apple_health_data\\export.xml")

#transform xml file to data frame - select the Record rows from the xml file
df <- XML:::xmlAttrsToDataFrame(xml["//Record"])

alejio

require("RSQLite")
# Set up database
drv <- dbDriver("SQLite")
tfile <- "Iowa.db"
con <- dbConnect(drv, dbname = "Iowa.db")
dbWriteTable(con, "data1", as.data.frame(data1))
dbDisconnect(con)

xpepper

Mac OS X

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