{"id":980,"date":"2020-07-06T10:01:44","date_gmt":"2020-07-06T13:01:44","guid":{"rendered":"https:\/\/micheladrianomedeiros.com.br\/blog\/?p=980"},"modified":"2020-07-06T10:20:26","modified_gmt":"2020-07-06T13:20:26","slug":"data-science-com-python-4","status":"publish","type":"post","link":"https:\/\/micheladrianomedeiros.com.br\/blog\/data-science-com-python-4\/","title":{"rendered":"Data Science Com Python #4"},"content":{"rendered":"\n

Lendo e Escrevendo Dados<\/strong><\/h4>\n\n\n\n

A habilidade de ler e escrever dados \u00e9 fundamental para trabalhar com qualquer ci\u00eancia de dados. A maioria dos tipos b\u00e1sicos de dados s\u00e3o texto e CSV (Comma Separated Values).<\/p>\n\n\n\n

O c\u00f3digo de exemplo l\u00ea um arquivo de texto e limpa o processo. Em seguida l\u00ea um arquivo de texto pr\u00e9-limpo, salve-o como um arquivo CSV, leia o arquivo CSV, converta para uma lista de elementos OrderedDict, e converta essa lista para a lista de elementos regulares do dicion\u00e1rio.<\/p>\n\n\n\n

Fa\u00e7a o download da pasta data para o exemplo funcionar.<\/a> <\/p>\n\n\n\n

import csv\n\ndef read_txt(f):\n    with open(f, 'r') as f:\n        d = f.readlines()\n        return [x.strip() for x in d]\n\ndef conv_csv(t, c):\n    data = read_txt(t)\n    with open(c, 'w', newline='') as csv_file:\n        writer = csv.writer(csv_file)\n        for line in data:\n            ls = line.split()\n            writer.writerow(ls)\n\ndef read_csv(f):\n    contents = ''\n    with open(f, 'r') as f:\n        reader = csv.reader(f)\n        return list(reader)\n\ndef read_dict(f, h):\n    input_file = csv.DictReader(open(f), fieldnames=h)\n    return input_file\n\ndef od_to_d(od):\n    return dict(od)\n\nif __name__ == \"__main__\":\n    f = 'data\/names.txt'\n    data = read_txt(f)\n    print ('text file data sample:')\n    for i, row in enumerate(data):\n        if i < 3:\n            print (row)\n    csv_f = 'data\/names.csv'\n    conv_csv(f, csv_f)\n    r_csv = read_csv(csv_f)\n    print ('\\ntext to csv sample:')\n    for i, row in enumerate(r_csv):\n        if i < 3:\n            print (row)\n    headers = ['first', 'last']\n    r_dict = read_dict(csv_f, headers)\n    dict_ls = []\n    print ('\\ncsv to ordered dict sample:')\n    for i, row in enumerate(r_dict):\n        r = od_to_d(row)\n        dict_ls.append(r)\n        if i < 3:\n            print (row)\n    print ('\\nlist of dictionary elements sample:')\n    for i, row in enumerate(dict_ls):\n        if i < 3:\n            print (row)\n<\/pre><\/div>\n\n\n\n