Created
February 10, 2017 20:51
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import pandas as pd | |
from scipy import stats | |
def print_output(stat, val): | |
print("The {0} for the Alcohol and Tobacco dataset is {1}.".format(stat, val)) | |
data = '''Region,Alcohol,Tobacco | |
North,6.47,4.03 | |
Yorkshire,6.13,3.76 | |
Northeast,6.19,3.77 | |
East Midlands,4.89,3.34 | |
West Midlands,5.63,3.47 | |
East Anglia,4.52,2.92 | |
Southeast,5.89,3.20 | |
Southwest,4.79,2.71 | |
Wales,5.27,3.53 | |
Scotland,6.08,4.51 | |
Northern Ireland,4.02,4.56''' | |
data = data.splitlines() | |
data = [i.split(',') for i in data] | |
column_names = data[0] # this is the first row | |
data_rows = data[1::] # these are all the following rows of data | |
df = pd.DataFrame(data_rows, columns=column_names) | |
df_al = df['Alcohol'].astype(float) | |
df_to = df['Tobacco'].astype(float) | |
frames = [df_al, df_to] | |
result = pd.concat(frames) | |
val_mean = result.mean() | |
val_median = result.median() | |
val_mode = stats.mode(result) | |
val_range = max(result)-min(result) | |
val_variance = result.var() | |
val_std = result.std() | |
print_output('mean', val_mean) | |
print_output('median', val_median) | |
print_output('mode', val_mode) | |
print_output('range', val_range) | |
print_output('variance', val_variance) | |
print_output('stadard deviation', val_std) |
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