DataCamp: Importing Data in Python (Part 1)

data_camp5.py

import numpy

# Print the keys of the MATLAB dictionary
print(mat.keys())

# Print the type of the value corresponding to the key 'CYratioCyt'
print(type(mat['CYratioCyt']))

# Print the shape of the value corresponding to the key 'CYratioCyt'
print(numpy.shape(mat['CYratioCyt']))

# Subset the array and plot it
data = mat['CYratioCyt'][25, 5:]
fig = plt.figure()
plt.plot(data)
plt.xlabel('time (min.)')
plt.ylabel('normalized fluorescence (measure of expression)')
plt.show()

data_camp5_2.py

from sqlalchemy import create_engine
import pandas as pd

engine = create_engine('sqlite:///Chinook.sqlite')

# Open engine in context manager
# Perform query and save results to DataFrame: df
with engine.connect() as con:
    rs = con.execute('SELECT LastName, Title FROM Employee')
    df = pd.DataFrame(rs.fetchmany(size=3))
    df.columns = rs.keys()

# Print the length of the DataFrame df
print(len(df))

# Print the head of the DataFrame df
print(df.head())

data_camp5_3.py

# Import packages
from sqlalchemy import create_engine
import pandas as pd

# Create engine: engine
engine = create_engine('sqlite:///Chinook.sqlite')

# Execute query and store records in DataFrame: df
df = pd.read_sql_query('SELECT * FROM Album', engine)

# Print head of DataFrame
print(df.head())