randyzwitch

#Loop over df and accumulate results
parsed_df <- data.frame()
for(i in 1:nrow(df)){
  temp <- cbind(df[i,],breakdown_list[[i]])
  parsed_df <- rbind(parsed_df, temp)
}

There were 12 warnings (use warnings() to see them)
>warnings()
Warning messages:

randyzwitch

#Loop over df and accumulate results
#Adding row.names = NULL fixes error message
parsed_df <- data.frame()
for(i in 1:nrow(df)){
  temp <- cbind(df[i,],breakdown_list[[i]], row.names = NULL)
  parsed_df <- rbind(parsed_df, temp)
}

names(parsed_df)

randyzwitch

#Separate breakdown list and original data frame into different objects
df <- ex_df$report$data
breakdown_list <- df$breakdown
df$breakdown <- NULL

#Loop over df and accumulate results
parsed_df <- data.frame()
for(i in 1:nrow(df)){
  right_df <-  breakdown_list[[i]]
  right_df <- rename(right_df, replace=c("name" = report_raw$report$elements$id[2]))

randyzwitch

               _
   _       _ _(_)_     |  A fresh approach to technical computing
  (_)     | (_) (_)    |  Documentation: http://docs.julialang.org
   _ _   _| |_  __ _   |  Type "help()" to list help topics
  | | | | | | |/ _` |  |
  | | |_| | | | (_| |  |  Version 0.3.0-prerelease+4028 (2014-07-02 23:42 UTC)
 _/ |\__'_|_|_|\__'_|  |  Commit 2185bd1 (11 days old master)
|__/                   |  x86_64-w64-mingw32

julia> using ODBC

randyzwitch

#Starting portion of query, the groupby columns
julia> groupbycols ="select
interact.interactionid,
interact.agentname,
interact.agentid,
interact.agentgroup,
interact.agentsupervisor,
interact.sitename,
interact.dnis,
interact.agentextension,

randyzwitch

library(ggplot2)

#Load Data
#Make sure months stay ordered - first time I ever wanted a factor!
#Label x-axis with every fifth label
visits_visitors <- read.csv("visits_visitors.csv")
visits_visitors$Month <- factor(visits_visitors$Month, levels = visits_visitors$Month, ordered = TRUE)
visits_visitors$Month_ <- ifelse(as.numeric(row.names(visits_visitors)) %% 5 == 0, as.character(visits_visitors$Month), "")

#Build plot as a series of elements

randyzwitch

import pandas as pd
import matplotlib.pyplot as plt
%matplotlib inline

#Read data into Python
dataset= pd.read_csv("visits_visitors.csv")

#Create every fifth month label
dataset["Month_"]= [value if (position+1) % 5 == 0 else "" for position, value in enumerate(dataset.Month)]

randyzwitch

import seaborn as sns
import matplotlib.pyplot as plt

#Set theme and size, remove axis titles
sns.set_style("whitegrid")
sns.set_context({"figure.figsize": (17, 6)}) #Passing in matplotlib commands directly

#Plot data
#Use dataset.index as my x_order, to ensure proper ordering by using numeric series
sns_views = sns.barplot(dataset.Month, "Views", data = dataset, color = "#278DBC", dropna = False, ci=None, x_order=dataset.Month)

randyzwitch

using Gadfly, DataFrames
set_default_plot_size(24cm, 8.5cm)

#Read in data using DataFrames package
df = readtable("visits_visitors.csv")

#Fill :Visitors with 0 to replace NA
df[:Visitors] = array(df[:Visitors], 0)

plot(df,

randyzwitch

using Plotly, DataFrames
Plotly.signin("username", "api-key")

#Read in data
df = readtable("visits_visitors.csv")

#Create page views plot
views = [
  ["x" => df[:Month], "y" => df[:Views], "type" => "bar", "name" => "Views", "marker" => ["color" => "rgb(39, 141, 188)"]]
]