<jupyter_start><jupyter_text>1. Import Libraries<jupyter_code>import pandas as pd
import numpy as np
import matplotlib.pyplot as plt<jupyter_output><empty_output><jupyter_text>2. Import Dataset<jupyter_code>url ="https://raw.githubusercontent.com/WalePhenomenon/climate_change/master/fuel_ferc1.csv"
df = pd.read_csv(url,error_bad_lines = False)


df.head(3)
print(df.shape)
df.corr()
df.describe()
df.isnull().sum()
df.info()
df.nunique()
df.dropna().head(3)
df.skew()
df.kurt()
#fig = plt.figure(figsize =(10, 7))	
#plt.bar(df["fuel_cost_per_unit_burned"].mean(),df['fuel_type_code_pudl'])
#fig = plt.figure(figsize =(10, 7))
#plt.bar(df['report_year'],df["fuel_cost_per_unit_delivered"].mean())
df["fuel_cost_per_unit_delivered"].groupby(by=df['report_year']).mean()
pd.set_option('display.max_rows', 500)
df["fuel_cost_per_unit_burned"].groupby(by=df['fuel_type_code_pudl']).mean()
pd.set_option("display.max_rows", 500)
df["fuel_cost_per_unit_burned"].groupby(by=[df['report_year'],df['fuel_type_code_pudl']] ).sum()<jupyter_output><empty_output>
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