!head -5 data/iris.csv

from into import into
into(list, 'data/iris.csv')[:5]

import numpy as np
into(np.ndarray, 'data/iris.csv')[:5]

into('sqlite:///data/my.db::iris', 'data/iris.csv')

from into import into

import numpy as np
into(np.ndarray, [1, 2, 3])

into(set, [1, 2, 3])

import pandas as pd
into(pd.Series, (10, 20, 30))

df = pd.DataFrame([['Alice',   100],
                   ['Bob',     200],
                   ['Charlie', 300]], columns=['name', 'balance'])

# Turn df into an np.ndarray
# into(..., ...)

# Turn df into a list
# into(..., ...)



target = []
into(target, (1, 2, 3))
into(target, (1, 2, 3))
into(target, (1, 2, 3))
target

L = [pd.DataFrame({'name': ['Alice', 'Bob'], 'balance': [100, 200]}),
     pd.DataFrame({'name': ['Charlie', 'Dan'], 'balance': [300, 400]}),
     pd.DataFrame({'name': ['Edith', 'Frank'], 'balance': [500, 600]})]

s = set()
# Use into and some kind of for loop to put all of the data in L into the set s




t = tuple()




# Write DataFrame to CSV file
into('accounts.csv', df)

# print out text in accounts.csv
!head accounts.csv

# Read CSV file into memory as list
into(list, 'accounts.csv')









into(list, 'sqlite:///data/lahman2013.sqlite::BattingPost')[:5]

from into import resource
t = resource('sqlite:///data/lahman2013.sqlite::BattingPost')

type(t)

t

into(list, t)[:5]













into('accounts.json', df)
!head accounts.json

!rm accounts.json  # Remove old file