Dropping Columns

import pandas as pd

df = pd.read_csv('amazon_fires.csv', encoding = "ISO-8859-1")

new_column_name = { 'ano' : 'year' ,  'mes': 'month', 'estado': 'state',
                   'numero': 'fire_numbers','encontro': 'date'}
                                                
df.rename(columns= new_column_name , inplace=True)   

Month_in_English = {'Janeiro': 'January',
'Fevereiro': 'February',
'Março': 'March',
'Abril': 'April',
'Maio': 'May',
'Junho': 'June',
'Julho': 'July',
'Agosto': 'August',
'Setembro': 'September',
'Outubro': 'October',
'Novembro': 'November',
'Dezembro': 'December'}

df["month"] = df["month"].map(Month_in_English)

new_column_order = [4,1,0,2,3,]

df = df[df.columns[new_column_order]]

df['fire_numbers'] = df['fire_numbers'].str.strip(" Fires")

df['fire_numbers'] = df['fire_numbers'].astype(float)

df = df.dropna() 

df.head()

	date	month	year	state	fire_numbers
0	1/1/1998	January	1998	Acre	0.0
1	1/1/1999	January	1999	Acre	0.0
2	1/1/2000	January	2000	Acre	0.0
3	1/1/2001	January	2001	Acre	0.0
4	1/1/2002	January	2002	Acre	0.0

Dropping a Column

df = df.drop(["month"], axis=1)

df.head()

	date	year	state	fire_numbers
0	1/1/1998	1998	Acre	0.0
1	1/1/1999	1999	Acre	0.0
2	1/1/2000	2000	Acre	0.0
3	1/1/2001	2001	Acre	0.0
4	1/1/2002	2002	Acre	0.0

Dropping Multiple Columns

df = df.drop(["month" , "year"], axis=1)

df.head()

	date	state	fire_numbers
0	1/1/1998	Acre	0.0
1	1/1/1999	Acre	0.0
2	1/1/2000	Acre	0.0
3	1/1/2001	Acre	0.0
4	1/1/2002	Acre	0.0