From 077b0fbcd9c6a6ad17f7ab811a27555924c081a6 Mon Sep 17 00:00:00 2001
From: William Carroll <wpcarro@gmail.com>
Date: Wed, 6 Oct 2021 16:36:51 -0700
Subject: Add Ramp's technical assessment

More technical interviews
---
 assessments/ramp/solution-emacs-elixir-format.py | 29 ++++++++
 assessments/ramp/solution.py                     | 87 ++++++++++++++++++++++++
 2 files changed, 116 insertions(+)
 create mode 100644 assessments/ramp/solution-emacs-elixir-format.py
 create mode 100644 assessments/ramp/solution.py

(limited to 'assessments/ramp')

diff --git a/assessments/ramp/solution-emacs-elixir-format.py b/assessments/ramp/solution-emacs-elixir-format.py
new file mode 100644
index 000000000000..d0d948402001
--- /dev/null
+++ b/assessments/ramp/solution-emacs-elixir-format.py
@@ -0,0 +1,29 @@
+# The file '2010.census.txt' contains summary statistics from the 2010 United
+# States census including household income. The data is in an unspecified
+# format.
+
+# Find the average of the column called:
+
+#     'MEDIAN HOUSEHOLD INCOME'
+
+# Ideally the solution should be a command line script, of the form:
+
+#     $ ./solution [options] [file...]
+
+# The solution may be written in any language, Python is preferred but not
+# required.
+
+# Google, stack overflow, etc. usage is allowed.
+
+import requests
+
+url = "https://assets.tryramp.com/interview/census/2010.census.txt"
+
+def main():
+    res = requests.get(url)
+    if res.status not in {200}:
+        raise Exception("Unexpected status code: {}".format(res.status_code))
+    # download the content
+    # parse row
+    # select 'MEDIAN HOUSEHOLD INCOME' column
+    pass
diff --git a/assessments/ramp/solution.py b/assessments/ramp/solution.py
new file mode 100644
index 000000000000..28060bfb3c40
--- /dev/null
+++ b/assessments/ramp/solution.py
@@ -0,0 +1,87 @@
+# The file '2010.census.txt' contains summary statistics from the 2010 United
+# States census including household income. The data is in an unspecified
+# format.
+
+# Find the average of the column called:
+
+#     'MEDIAN HOUSEHOLD INCOME'
+
+# Ideally the solution should be a command line script, of the form:
+
+#     $ ./solution [options] [file...]
+
+# The solution may be written in any language, Python is preferred but not
+# required.
+
+# Google, stack overflow, etc. usage is allowed.
+
+import requests
+import csv
+
+url = "https://assets.tryramp.com/interview/census/2010.census.txt"
+column = 'MEDIAN HOUSEHOLD INCOME'
+columns = [
+    'CENSUS YEAR',
+    'TRACT',
+    'BLOCK GROUP',
+    'FIPS ID',
+    'TOTAL POPULATION',
+    'POPULATION WHITE',
+    'POPULATION BLACK',
+    'POPULATION ASIAN',
+    'POPULATION OTHER',
+    'POPULATION AMERICAN INDIAN',
+    'POPULATION PACIFIC ISLANDER',
+    'POPULATION ONE RACE',
+    'POPULATION MULTI RACE',
+    'POPULATION 25 OLDER',
+    'MEDIAN AGE',
+    'MEDIAN HOUSEHOLD INCOME',
+    'HIGH SCHOOL MALE',
+    'HIGH SCHOOL MORE MALE',
+    'COLLEGE 1 YR LESS MALE',
+    'COLLEGE 1 YR MORE MALE',
+    'ASSOCIATES DEGREE MALE',
+    'BACHELORS DEGREE MALE',
+    'MASTERS DEGREE MALE',
+    'PROFESSIONAL DEGREE MALE',
+    'DOCTORAL DEGREE MALE',
+    'HIGH SCHOOL FEMALE',
+    'HIGH SCHOOL MORE FEMALE',
+    'COLLEGE 1 YR LESS FEMALE',
+    'COLLEGE 1 YR MORE FEMALE',
+    'ASSOCIATES DEGREE FEMALE',
+    'BACHELORS DEGREE FEMALE',
+    'MASTERS DEGREE FEMALE',
+    'PROFESSIONAL DEGREE FEMALE',
+    'DOCTORAL DEGREE FEMALE',
+    'PERCENT 25 YR OVER HIGH SCHOOL MORE',
+    'HOUSING UNITS',
+    'OCCUPIED HOUSING UNITS',
+    'OWNER OCCUPIED HOUSING',
+    'RENTER OCCUPIED HOUSING',
+    'PERCENT OWNER OCCUPIED',
+    'PERCENT RENTER OCCUPIED',
+    'MEDIAN HOUSE VALUE OWNER OCCUPIED',
+    'MEDIAN YEAR BUILT',
+    'VACANCY RATES',
+]
+
+
+def average(xs):
+    return sum(xs) / len(xs)
+
+
+def parse_body(body):
+    return list(csv.DictReader(body.split('\n')[1:], delimiter='|', fieldnames=columns))
+
+
+def main():
+    res = requests.get(url)
+    if res.status_code not in {200}:
+        raise Exception("Unexpected status code: {}".format(res.status_code))
+    return average([int(d.get(column))
+                    for d in parse_body(res.text)
+                    if int(d.get(column)) >= 0])
+
+print(main())
-- 
cgit 1.4.1