gistfile1.py

import csv
import json


with open('metrics.json', 'r') as f:
    data = json.load(f)
keys = data[0].keys()
writer = csv.DictWriter(open('metrics.csv', 'wb'), keys)
writer.writer.writerow(keys)
writer.writerows(data)

gistfile2.r

library(ggplot2)
library(scales)

dn <- read.csv('metrics.csv', sep=',')
dn$timestamp <- as.POSIXlt(dn$timestamp, origin='1970-01-01',tz='UTC', 
                           format="%Y-%m-%d %H:%M:%S")
dn$value <- as.numeric(dn$value)

dnf <- dn[dn$network == 'SoundCloud' & dn$metric=='plays' & dn$network_id == '10531558' ,]

lm1 <- lm(as.numeric(dnf$timestamp) ~ dnf$value)

ggplot(dnf, aes(timestamp, lm1$residuals)) + 
  geom_point() +
  facet_wrap(~network_id + network + metric) +
  scale_x_datetime(breaks=date_breaks('6 hours')) + 
  theme(axis.text.x = element_text(angle = 90, hjust = 0)) +
  ylab('residuals')