{"id":3515,"date":"2023-07-17T02:11:32","date_gmt":"2023-07-17T02:11:32","guid":{"rendered":"https:\/\/statorials.org\/pt\/pandas-multiplicam-duas-colunas\/"},"modified":"2023-07-17T02:11:32","modified_gmt":"2023-07-17T02:11:32","slug":"pandas-multiplicam-duas-colunas","status":"publish","type":"post","link":"https:\/\/statorials.org\/pt\/pandas-multiplicam-duas-colunas\/","title":{"rendered":"Como multiplicar duas colunas em pandas: com exemplos"},"content":{"rendered":"

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Voc\u00ea pode usar os seguintes m\u00e9todos para multiplicar duas colunas em um DataFrame do pandas:<\/span><\/p>\n

M\u00e9todo 1: Multiplicar duas colunas<\/strong><\/span><\/p>\n

 df[' new_column<\/span> '] = df. column1<\/span> * df. column2<\/span><\/strong><\/pre>\n
 M\u00e9todo 2: Multiplique duas colunas com base na condi\u00e7\u00e3o<\/strong><\/span><\/p>\n
 new_column = df. column1<\/span> * df. column2<\/span>\n\n#update values based on condition\n<\/span>df[' new_column<\/span> '] = new_column. where<\/span> (df. column2<\/span> == ' value1<\/span> ', other= 0<\/span> )\n<\/strong><\/pre>\n
 Os exemplos a seguir mostram como usar cada m\u00e9todo na pr\u00e1tica.<\/span><\/p>\n
 Exemplo 1: Multiplique duas colunas<\/strong><\/span><\/h2>\n
 Suponha que temos o seguinte DataFrame do pandas:<\/span><\/span><\/p>\n
 import<\/span> pandas as<\/span> pd\n\n#createDataFrame\n<\/span>df = pd. DataFrame<\/span> ({' price<\/span> ': [22, 20, 25, 30, 4, 8, 12, 10],\n                   ' amount<\/span> ': [3, 1, 3, 3, 2, 4, 3, 5]})\n\n#view DataFrame\n<\/span>print<\/span> (df)\n\n   price amount\n0 22 3\n1 20 1\n2 25 3\n3 30 3\n4 4 2\n5 8 4\n6 12 3\n7 10 5<\/strong><\/pre>\n
 Podemos usar a seguinte sintaxe para multiplicar as colunas de pre\u00e7o<\/strong> e valor<\/strong> e criar uma nova coluna chamada receita<\/strong> :<\/span><\/p>\n
 #multiply price and amount columns\n<\/span>df[' revenue<\/span> '] = df. price<\/span> * df. amount<\/span>\n\n#view updated DataFrame\n<\/span>print<\/span> (df)\n\n   price amount revenue\n0 22 3 66\n1 20 1 20\n2 25 3 75\n3 30 3 90\n4 4 2 8\n5 8 4 32\n6 12 3 36\n7 10 5 50<\/strong><\/pre>\n
 Observe que os valores na nova coluna de receita<\/b> s\u00e3o o produto dos valores nas colunas Pre\u00e7o<\/strong> e Valor<\/strong> .<\/span><\/p>\n
 Exemplo 2: Multiplique duas colunas com base na condi\u00e7\u00e3o<\/strong><\/span><\/h2>\n
 Suponha que temos o seguinte DataFrame do pandas:<\/span><\/p>\n
 import<\/span> pandas as<\/span> pd<\/span>\n\n#createDataFrame<\/span>\ndf = pd. DataFrame<\/span> ({' price<\/span> ': [22, 20, 25, 30, 4, 8, 12, 10],\n                   ' amount<\/span> ': [3, 1, 3, 3, 2, 4, 3, 5],\n                   ' type<\/span> ': ['Sale', 'Refund', 'Sale', 'Sale',\n                            'Sale', 'Refund', 'Refund', 'Sale']})\n\n#view DataFrame\n<\/span>print<\/span> (df)\n\n   price amount type\n0 22 3 Dirty\n1 20 1 Refund\n2 25 3 Dirty\n3 30 3 Dirty\n4 4 2 Dirty\n5 8 4 Refund\n6 12 3 Return\n7 10 5 Dirty<\/strong><\/pre>\n
 Podemos multiplicar as colunas de pre\u00e7o<\/strong> e quantidade<\/strong> e, em seguida, usar a fun\u00e7\u00e3o where ()<\/strong> para alterar os resultados com base no valor da coluna de tipo<\/strong> :<\/span><\/p>\n
 #multiply price and amount columns\n<\/span>income = df. price<\/span> * df. amount<\/span>\n\n#update values based on type\n<\/span>df[' revenue<\/span> '] = revenue. where<\/span> (df. type<\/span> == ' Sale<\/span> ', other= 0<\/span> )\n\n#view updated DataFrame\n<\/span>print<\/span> (df)\n\n   price amount type revenue\n0 22 3 Dirty 66\n1 20 1 Refund 0\n2 25 3 Dirty 75\n3 30 3 Dirty 90\n4 4 2 Dirty 8\n5 8 4 Refund 0\n6 12 3 Refund 0\n7 10 5 Dirty 50<\/strong><\/pre>\n
 Observe que a coluna Renda<\/b> assume os seguintes valores:<\/span><\/p>\n