Question

我有一个存储在csv文件中的数据，如下面的格式

892,3,"Kelly, Mr. James",male,34.5,0,0,330911,7.8292,,Q
893,3,"Wilkes, Mrs. James (Ellen Needs)",female,47,1,0,363272,7,,S
894,2,"Myles, Mr. Thomas Francis",male,62,0,0,240276,9.6875,,Q
895,3,"Wirz, Mr. Albert",male,27,0,0,315154,8.6625,,S
896,3,"Hirvonen, Mrs. Alexander (Helga E Lindqvist)",female,22,1,1,3101298,12.2875,,S
897,3,"Svensson, Mr. Johan Cervin",male,14,0,0,7538,9.225,,S

每个列的数据类型

1. int        6. int
2. int        7. int
3. String     8. float
4. String     9. float
5. float      10.String
              11.String

以 892,893，... 897 开头的第一列应以int格式存储在array中。像“威尔克斯，詹姆斯夫人（Ellen Needs）”这样的第三栏应该存储在string类型中。但是，第三列是string格式，但字符的长度是不是固定，即我不知道此列中存储的字符的最大长度

我做过：

 csv_file_object = csv.reader(open('trainData.csv', 'rb'))
 header = csv_file_object.next()

 data=[]
 for row in csv_file_object:
    data.append(row)
    data = np.array(data)

但是，上面的代码将所有列读为string，但其中许多不是string格式，并将信息存储在string格式。另一方面，如果我使用genfromtxt，第三列是问题，因为它包含双配额内的逗号。

我希望每个列都有自己的数据类型，即第一列应该存储为int类型。

我预期的数组：

892 3 "Kelly, Mr. James" male 34.5 0 0 330911 7.8292 NaN Q
893 3 "Wilkes, Mrs. James (Ellen Needs)" female 47 1 0 363272 7 NaN S
894 2 "Myles, Mr. Thomas Francis" male 62 0 0 240276 9.6875 NaN Q
895 3 "Wirz, Mr. Albert" male 27 0 0 315154 8.6625 NaN S
896 3 "Hirvonen, Mrs. Alexander (Helga E Lindqvist)" female 22 1 1 3101298 12.2875 NaN S
897 3 "Svensson, Mr. Johan Cervin" male 14 0 0 7538 9.225 S

如您所见，如果数据不可用，则应放置NaN或其衍生物。

我应该阅读什么csv文件？

Answer 1

我不确定我是否理解你，但我认为这对你有用。

我实现了另外两个函数，它们将决定字符串是浮点数还是整数。

如果字符串是空字符串，我写了None，但是，您可以将其更改为您喜欢的任何内容。

import csv
import numpy as np

def isfloat(x):
    try:
        a = float(x)
    except ValueError:
        return False
    else:
        return True

def isint(x):
    try:
        a = float(x)
        b = int(a)
    except ValueError:
        return False
    else:
        return a == b


csv_file_object = csv.reader(open('trainData.csv', 'rb'))
header = csv_file_object

data=[]
for row in csv_file_object:
    for index, cell in enumerate(row):
        if isint(cell):
            row[index] = int(cell)
        elif isfloat(cell):
            row[index] = float(cell)
        if not cell: # cell == ''
            row[index] = None  # you can change the value to whatever you like.
    data.append(row)

print data

<强>输出：

[[892, 3, 'Kelly, Mr. James', 'male', 34.5, 0, 0, 330911, 7.8292, None, 'Q'],
 [893, 3, 'Wilkes, Mrs. James (Ellen Needs)', 'female', 47, 1, 0, 363272, 7, None, 'S'],
 [894, 2, 'Myles, Mr. Thomas Francis', 'male', 62, 0, 0, 240276, 9.6875, None, 'Q'],
 [895, 3, 'Wirz, Mr. Albert', 'male', 27, 0, 0, 315154, 8.6625, None, 'S'],
 [896, 3, 'Hirvonen, Mrs. Alexander (Helga E Lindqvist)', 'female', 22, 1, 1, 3101298, 12.2875, None, 'S'],
 [897, 3, 'Svensson, Mr. Johan Cervin', 'male', 14, 0, 0, 7538, 9.225, None, 'S']]

Answer 2

您可以更轻松地使用pandas库，如下所示：

import pandas as pd

df = pd.read_csv("trainData.csv", dtype={'col1': int, 'col2': int, 'col3': str, 'col4': str, 'col5': float, 'col6':int,
                                  'col7': int, 'col8': float, 'col9':float, 'col10': str, 'col11': str})
df = map(list, df.values)
print df

<强>输出：

[[892, 3, 'Kelly, Mr. James', 'male', 34.5, 0, 0, 330911.0, 7.8292, nan, 'Q'],
 [893, 3, 'Wilkes, Mrs. James (Ellen Needs)', 'female', 47.0, 1, 0, 363272.0, 7.0, nan, 'S'],
 [894, 2, 'Myles, Mr. Thomas Francis', 'male', 62.0, 0, 0, 240276.0, 9.6875, nan, 'Q'],
 [895, 3, 'Wirz, Mr. Albert', 'male', 27.0, 0, 0, 315154.0, 8.6625, nan, 'S'],
 [896, 3, 'Hirvonen, Mrs. Alexander (Helga E Lindqvist)', 'female', 22.0, 1, 1, 3101298.0, 12.2875, nan, 'S'],
 [897, 3, 'Svensson, Mr. Johan Cervin', 'male', 14.0, 0, 0, 7538.0, 9.225, nan, 'S']]

csv文件应该如下所示，因为第一行是列名

col1,col2,col3,col4,col5,col6,col7,col8,col9,col10,col11
892,3,"Kelly, Mr. James",male,34.5,0,0,330911,7.8292,,Q
893,3,"Wilkes, Mrs. James (Ellen Needs)",female,47,1,0,363272,7,,S
894,2,"Myles, Mr. Thomas Francis",male,62,0,0,240276,9.6875,,Q
895,3,"Wirz, Mr. Albert",male,27,0,0,315154,8.6625,,S
896,3,"Hirvonen, Mrs. Alexander (Helga E Lindqvist)",female,22,1,1,3101298,12.2875,,S
897,3,"Svensson, Mr. Johan Cervin",male,14,0,0,7538,9.225,,S

您可以在此处阅读有关pandas的更多信息http://pandas.pydata.org/pandas-docs/stable/tutorials.html

Answer 3

我假设您正在使用熊猫，因为问题是标记为pandas。像这样读取文件：

df = pd.read_csv('test.txt', skiprows=0, index_col=0, 
            names='city_type name sex weight has_cat has_dog bank_balance body_fat_index car_mileage car_type'.split())

您将获得如下数据框： enter image description here

我冒昧地为列编制名称。

一旦你将数据读入数据框，就可以用它做各种各样的魔术 - 看看pandas教程（它们很棒）。这是一个例子

df.bank_balance.describe()

count          6.000000
mean      726408.166667
std      1170522.652019
min         7538.000000
25%       258995.500000
50%       323032.500000
75%       355181.750000
max      3101298.000000
Name: bank_balance, dtype: float64

如何阅读csv

3 个答案: