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# # Data dictionary first steps
#
# I am going to be using this notebook to help create a data dictionary and put together descriptive/summary statistics for final_db. Work in progress.

# +
from util_functions import *
import numpy as np
import pandas as pd

set_env_path()
conn, cur = aws_connect()
query = """
SELECT *
from final_db"""

pd.options.display.max_rows = 999
df = pd.read_sql(query, con=conn)
df.describe(percentiles=[.5]).round().transpose()
# -

# ### Breaking it down
# * There are a number of sources for our final_db data (in order of appearance)
#   * DarkSky - weather data
#   * Misc - population, bike event, and nats games data
#   * CaBi - Capital Bikeshare
#     * To fill in later
#   * Dockless - various dockless companies by way of DDOT
#     * Number of trips, trip distance (total and average), geographic data, duration, number of users, and number of bikes
#   



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