ianmcook

C:\Users\ian>vcpkg install --clean-after-build --triplet x64-windows --x-manifest-root C:\Users\ian\arrow\cpp
A suitable version of cmake was not found (required v3.19.2). Downloading portable cmake v3.19.2...
Downloading cmake...
  https://github.com/Kitware/CMake/releases/download/v3.19.2/cmake-3.19.2-win32-x86.zip -> C:\vcpkg\downloads\cmake-3.19.2-win32-x86.zip
Extracting cmake...
A suitable version of 7zip was not found (required v18.1.0). Downloading portable 7zip v18.1.0...
Downloading 7zip...
  https://www.nuget.org/api/v2/package/7-Zip.CommandLine/18.1.0 -> C:\vcpkg\downloads\7-zip.commandline.18.1.0.nupkg
Extracting 7zip...
A suitable version of nuget was not found (required v5.5.1). Downloading portable nuget v5.5.1...

ianmcook

install.packages(c("ggmap", "leaflet", "sp"))
devtools::install_github("ianmcook/weatherAlerts")
devtools::install_github("ianmcook/weatherAlertAreas")

# geocode home address
library(ggmap)
register_google("ENTER_GCP_GEOCODING_API_KEY_HERE")
home <- geocode("University of North Carolina at Chapel Hill")

# or specify coordinates of home

ianmcook

# enquo() helpers for eager evaluation and idempotence

# wrap eager() around enquo() to evaluate the quosure immediately in the calling
# environment *if* it can do so without error, otherwise return the quosure
eager <- function(quo) {
  val <- try(eval_tidy(quo), silent = TRUE)
  if (inherits(val, "try-error")) {
    quo
  } else {
    val

ianmcook

# Copyright 2018 Cloudera, Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,

ianmcook

#include <iostream>
#include <arrow/api.h>
#include <arrow/result.h>
#include <arrow/compute/api.h>

arrow::Status Execute() {
  arrow::Int32Builder int_builder;
  ARROW_RETURN_NOT_OK(int_builder.Append(1));
  ARROW_RETURN_NOT_OK(int_builder.Append(2));
  ARROW_RETURN_NOT_OK(int_builder.Append(3));

ianmcook

# run this script second

library(dplyr)

df <- read.csv("dirty.csv")

agg <- df %>%
  group_by(jira, github) %>%
  summarise(n = n(), .groups = "keep") %>%
  ungroup() %>%

ianmcook

# pip install 'ibis-framework[duckdb]'

import pandas as pd
import ibis
from ibis import _

# create a pandas DataFrame and write it to a Parquet file
df = pd.DataFrame(data={'repo': ['pandas', 'duckdb', 'ibis'],
                        'stars': [36622, 8074, 2336]})
df.to_parquet('repo_stars.parquet')

ianmcook

#include <iostream>
#include <arrow/api.h>
#include <arrow/result.h>
#include <arrow/compute/api.h>
#include <arrow/compute/exec/exec_plan.h>

arrow::Status ExecutePlanAndCollectAsTable(
  std::shared_ptr<arrow::compute::ExecPlan> plan,
  std::shared_ptr<arrow::Schema> schema,
  arrow::AsyncGenerator<std::optional<arrow::compute::ExecBatch>> sink_gen) {

ianmcook

# before running:
# 1. install Ibis and its Trino backend: https://ibis-project.org/backends/Trino/
# 2. pull and run the Trino docker container: https://trino.io/docs/current/installation/containers.html

import ibis
from ibis import _

# connect to Trino
conn = ibis.trino.connect(database='memory', schema='default')

ianmcook

# before running:
# 1. install Ibis and its Snowflake backend: https://ibis-project.org/backends/Snowflake/
# 2. create and activate a Snowflake trial account
# 3. set environment variables SNOWSQL_USER, SNOWSQL_PWD, SNOWSQL_ACCOUNT

import os
import ibis
from ibis import _

ibis.options.interactive = True