<jupyter_start><jupyter_text>**Hamoye Stage 1 assessment**<jupyter_code>import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
url='https://github.com/WalePhenomenon/climate_change/blob/master/fuel_ferc1.csv?raw=true'
fuel_data = pd.read_csv(url, error_bad_lines=False)
print(fuel_data)
fuel_data.describe(include='all')
fuel_data.groupby('fuel_unit')['fuel_unit'].count()
fuel_data[['fuel_unit']] = fuel_data[['fuel_unit']].fillna(value='mcf')
fuel_data.isnull().sum()
fuel_data.groupby('report_year')['report_year'].count()
fuel_data.groupby('fuel_type_code_pudl').first()
fuel_data.duplicated().any()
fuel_data.isnull().sum()
fuel_data.describe()
from scipy.stats import skew
skew(fuel_data['fuel_cost_per_mmbtu'])
print(fuel_data)
print(fuel_data['fuel_unit'])
fuel_data.isnull()
missing_fuel_data=fuel_data.isna
print(missing_fuel_data)
missing_fuel_data=fuel_data.isnull()
print(missing_fuel_data)
missing_fuel_data.sum()<jupyter_output><empty_output><jupyter_text>Data Set above has no null values since it was **dropped** Running in new note_book, I get **180**<jupyter_code>fuel_data.groupby('report_year').mean()
from scipy.stats import kurtosis
kurtosis(fuel_data["fuel_qty_burned"])
skew(fuel_data['fuel_qty_burned'])<jupyter_output><empty_output>
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