这篇文章主要介绍TensorFlow如何读取CSV数据，文中介绍的非常详细，具有一定的参考价值，感兴趣的小伙伴们一定要看完！
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方法一：
详细读取tf_read.csv 代码
#coding:utf-8
import tensorflow as tf
filename_queue = tf.train.string_input_producer(["/home/yongcai/tf_read.csv"])
reader = tf.TextLineReader()
key, value = reader.read(filename_queue)
record_defaults = [[1.], [1.], [1.], [1.]]
col1, col2, col3, col4 = tf.decode_csv(value, record_defaults=record_defaults)
features = tf.stack([col1, col2, col3])
init_op = tf.global_variables_initializer()
local_init_op = tf.local_variables_initializer()
with tf.Session() as sess:
sess.run(init_op)
sess.run(local_init_op)
# Start populating the filename queue.
coord = tf.train.Coordinator()
threads = tf.train.start_queue_runners(coord=coord)
try:
for i in range(30):
example, label = sess.run([features, col4])
print(example)
# print(label)
except tf.errors.OutOfRangeError:
print 'Done !!!'
finally:
coord.request_stop()
coord.join(threads)
tf_read.csv 数据：
-0.76 15.67 -0.12 15.67
-0.48 12.52 -0.06 12.51
1.33 9.11 0.12 9.1
-0.88 20.35 -0.18 20.36
-0.25 3.99 -0.01 3.99
-0.87 26.25 -0.23 26.25
-1.03 2.87 -0.03 2.87
-0.51 7.81 -0.04 7.81
-1.57 14.46 -0.23 14.46
-0.1 10.02 -0.01 10.02
-0.56 8.92 -0.05 8.92
-1.2 4.1 -0.05 4.1
-0.77 5.15 -0.04 5.15
-0.88 4.48 -0.04 4.48
-2.7 10.82 -0.3 10.82
-1.23 2.4 -0.03 2.4
-0.77 5.16 -0.04 5.15
-0.81 6.15 -0.05 6.15
-0.6 5.01 -0.03 5
-1.25 4.75 -0.06 4.75
-2.53 7.31 -0.19 7.3
-1.15 16.39 -0.19 16.39
-1.7 5.19 -0.09 5.18
-0.62 3.23 -0.02 3.22
-0.74 17.43 -0.13 17.41
-0.77 15.41 -0.12 15.41
0 47 0 47.01
0.25 3.98 0.01 3.98
-1.1 9.01 -0.1 9.01
-1.02 3.87 -0.04 3.87
方法二：
详细读取 Iris_train.csv, Iris_test.csv 代码
#coding:utf-8
import tensorflow as tf
import os
os.chdir("/home/yongcai/")
print(os.getcwd())
def read_data(file_queue):
reader = tf.TextLineReader(skip_header_lines=1)
key, value = reader.read(file_queue)
defaults = [[0], [0.], [0.], [0.], [0.], ['']]
Id, SepalLengthCm, SepalWidthCm, PetalLengthCm, PetalWidthCm, Species = tf.decode_csv(value, defaults)
preprocess_op = tf.case({
tf.equal(Species, tf.constant('Iris-setosa')): lambda: tf.constant(0),
tf.equal(Species, tf.constant('Iris-versicolor')): lambda: tf.constant(1),
tf.equal(Species, tf.constant('Iris-virginica')): lambda: tf.constant(2),
}, lambda: tf.constant(-1), exclusive=True)
return tf.stack([SepalLengthCm, SepalWidthCm, PetalLengthCm, PetalWidthCm]), preprocess_op
def create_pipeline(filename, batch_size, num_epochs=None):
file_queue = tf.train.string_input_producer([filename], num_epochs=num_epochs)
example, label = read_data(file_queue)
min_after_dequeue = 1000
capacity = min_after_dequeue + batch_size
example_batch, label_batch = tf.train.shuffle_batch(
[example, label], batch_size=batch_size, capacity=capacity,
min_after_dequeue=min_after_dequeue
)
return example_batch, label_batch
# x_train_batch, y_train_batch = create_pipeline('Iris-train.csv', 50, num_epochs=1000)
x_test, y_test = create_pipeline('Iris-test.csv', 60)
init_op = tf.global_variables_initializer()
local_init_op = tf.local_variables_initializer()
# output read data result
with tf.Session() as sess:
sess.run(init_op)
sess.run(local_init_op)
coord = tf.train.Coordinator()
thread = tf.train.start_queue_runners(coord=coord)
try:
example, label = sess.run([x_test, y_test])
print example
print label
except tf.errors.OutOfRangeError:
print 'Done !!!'
finally:
coord.request_stop()
coord.join(threads=thread)Iris_train.csv 数据：
Id SepalLengthCm SepalWidthCm PetalLengthCm PetalWidthCm Species
21 5.4 3.4 1.7 0.2 Iris-setosa
22 5.1 3.7 1.5 0.4 Iris-setosa
23 4.6 3.6 1 0.2 Iris-setosa
24 5.1 3.3 1.7 0.5 Iris-setosa
25 4.8 3.4 1.9 0.2 Iris-setosa
26 5 3 1.6 0.2 Iris-setosa
27 5 3.4 1.6 0.4 Iris-setosa
28 5.2 3.5 1.5 0.2 Iris-setosa
29 5.2 3.4 1.4 0.2 Iris-setosa
30 4.7 3.2 1.6 0.2 Iris-setosa
31 4.8 3.1 1.6 0.2 Iris-setosa
32 5.4 3.4 1.5 0.4 Iris-setosa
33 5.2 4.1 1.5 0.1 Iris-setosa
34 5.5 4.2 1.4 0.2 Iris-setosa
35 4.9 3.1 1.5 0.1 Iris-setosa
36 5 3.2 1.2 0.2 Iris-setosa
37 5.5 3.5 1.3 0.2 Iris-setosa
38 4.9 3.1 1.5 0.1 Iris-setosa
39 4.4 3 1.3 0.2 Iris-setosa
40 5.1 3.4 1.5 0.2 Iris-setosa
41 5 3.5 1.3 0.3 Iris-setosa
42 4.5 2.3 1.3 0.3 Iris-setosa
43 4.4 3.2 1.3 0.2 Iris-setosa
44 5 3.5 1.6 0.6 Iris-setosa
45 5.1 3.8 1.9 0.4 Iris-setosa
46 4.8 3 1.4 0.3 Iris-setosa
47 5.1 3.8 1.6 0.2 Iris-setosa
48 4.6 3.2 1.4 0.2 Iris-setosa
49 5.3 3.7 1.5 0.2 Iris-setosa
50 5 3.3 1.4 0.2 Iris-setosa
71 5.9 3.2 4.8 1.8 Iris-versicolor
72 6.1 2.8 4 1.3 Iris-versicolor
73 6.3 2.5 4.9 1.5 Iris-versicolor
74 6.1 2.8 4.7 1.2 Iris-versicolor
75 6.4 2.9 4.3 1.3 Iris-versicolor
76 6.6 3 4.4 1.4 Iris-versicolor
77 6.8 2.8 4.8 1.4 Iris-versicolor
78 6.7 3 5 1.7 Iris-versicolor
79 6 2.9 4.5 1.5 Iris-versicolor
80 5.7 2.6 3.5 1 Iris-versicolor
81 5.5 2.4 3.8 1.1 Iris-versicolor
82 5.5 2.4 3.7 1 Iris-versicolor
83 5.8 2.7 3.9 1.2 Iris-versicolor
84 6 2.7 5.1 1.6 Iris-versicolor
85 5.4 3 4.5 1.5 Iris-versicolor
86 6 3.4 4.5 1.6 Iris-versicolor
87 6.7 3.1 4.7 1.5 Iris-versicolor
88 6.3 2.3 4.4 1.3 Iris-versicolor
89 5.6 3 4.1 1.3 Iris-versicolor
90 5.5 2.5 4 1.3 Iris-versicolor
91 5.5 2.6 4.4 1.2 Iris-versicolor
92 6.1 3 4.6 1.4 Iris-versicolor
93 5.8 2.6 4 1.2 Iris-versicolor
94 5 2.3 3.3 1 Iris-versicolor
95 5.6 2.7 4.2 1.3 Iris-versicolor
96 5.7 3 4.2 1.2 Iris-versicolor
97 5.7 2.9 4.2 1.3 Iris-versicolor
98 6.2 2.9 4.3 1.3 Iris-versicolor
99 5.1 2.5 3 1.1 Iris-versicolor
100 5.7 2.8 4.1 1.3 Iris-versicolor
121 6.9 3.2 5.7 2.3 Iris-virginica
122 5.6 2.8 4.9 2 Iris-virginica
123 7.7 2.8 6.7 2 Iris-virginica
124 6.3 2.7 4.9 1.8 Iris-virginica
125 6.7 3.3 5.7 2.1 Iris-virginica
126 7.2 3.2 6 1.8 Iris-virginica
127 6.2 2.8 4.8 1.8 Iris-virginica
128 6.1 3 4.9 1.8 Iris-virginica
129 6.4 2.8 5.6 2.1 Iris-virginica
130 7.2 3 5.8 1.6 Iris-virginica
131 7.4 2.8 6.1 1.9 Iris-virginica
132 7.9 3.8 6.4 2 Iris-virginica
133 6.4 2.8 5.6 2.2 Iris-virginica
134 6.3 2.8 5.1 1.5 Iris-virginica
135 6.1 2.6 5.6 1.4 Iris-virginica
136 7.7 3 6.1 2.3 Iris-virginica
137 6.3 3.4 5.6 2.4 Iris-virginica
138 6.4 3.1 5.5 1.8 Iris-virginica
139 6 3 4.8 1.8 Iris-virginica
140 6.9 3.1 5.4 2.1 Iris-virginica
141 6.7 3.1 5.6 2.4 Iris-virginica
142 6.9 3.1 5.1 2.3 Iris-virginica
143 5.8 2.7 5.1 1.9 Iris-virginica
144 6.8 3.2 5.9 2.3 Iris-virginica
145 6.7 3.3 5.7 2.5 Iris-virginica
146 6.7 3 5.2 2.3 Iris-virginica
147 6.3 2.5 5 1.9 Iris-virginica
148 6.5 3 5.2 2 Iris-virginica
149 6.2 3.4 5.4 2.3 Iris-virginica
150 5.9 3 5.1 1.8 Iris-virginica
Iris_test.csv 数据：
Id SepalLengthCm SepalWidthCm PetalLengthCm PetalWidthCm Species
1 5.1 3.5 1.4 0.2 tf_read
2 4.9 3 1.4 0.2 Iris-setosa
3 4.7 3.2 1.3 0.2 Iris-setosa
4 4.6 3.1 1.5 0.2 Iris-setosa
5 5 3.6 1.4 0.2 Iris-setosa
6 5.4 3.9 1.7 0.4 Iris-setosa
7 4.6 3.4 1.4 0.3 Iris-setosa
8 5 3.4 1.5 0.2 Iris-setosa
9 4.4 2.9 1.4 0.2 Iris-setosa
10 4.9 3.1 1.5 0.1 Iris-setosa
11 5.4 3.7 1.5 0.2 Iris-setosa
12 4.8 3.4 1.6 0.2 Iris-setosa
13 4.8 3 1.4 0.1 Iris-setosa
14 4.3 3 1.1 0.1 Iris-setosa
15 5.8 4 1.2 0.2 Iris-setosa
16 5.7 4.4 1.5 0.4 Iris-setosa
17 5.4 3.9 1.3 0.4 Iris-setosa
18 5.1 3.5 1.4 0.3 Iris-setosa
19 5.7 3.8 1.7 0.3 Iris-setosa
20 5.1 3.8 1.5 0.3 Iris-setosa
51 7 3.2 4.7 1.4 Iris-versicolor
52 6.4 3.2 4.5 1.5 Iris-versicolor
53 6.9 3.1 4.9 1.5 Iris-versicolor
54 5.5 2.3 4 1.3 Iris-versicolor
55 6.5 2.8 4.6 1.5 Iris-versicolor
56 5.7 2.8 4.5 1.3 Iris-versicolor
57 6.3 3.3 4.7 1.6 Iris-versicolor
58 4.9 2.4 3.3 1 Iris-versicolor
59 6.6 2.9 4.6 1.3 Iris-versicolor
60 5.2 2.7 3.9 1.4 Iris-versicolor
61 5 2 3.5 1 Iris-versicolor
62 5.9 3 4.2 1.5 Iris-versicolor
63 6 2.2 4 1 Iris-versicolor
64 6.1 2.9 4.7 1.4 Iris-versicolor
65 5.6 2.9 3.6 1.3 Iris-versicolor
66 6.7 3.1 4.4 1.4 Iris-versicolor
67 5.6 3 4.5 1.5 Iris-versicolor
68 5.8 2.7 4.1 1 Iris-versicolor
69 6.2 2.2 4.5 1.5 Iris-versicolor
70 5.6 2.5 3.9 1.1 Iris-versicolor
101 6.3 3.3 6 2.5 Iris-virginica
102 5.8 2.7 5.1 1.9 Iris-virginica
103 7.1 3 5.9 2.1 Iris-virginica
104 6.3 2.9 5.6 1.8 Iris-virginica
105 6.5 3 5.8 2.2 Iris-virginica
106 7.6 3 6.6 2.1 Iris-virginica
107 4.9 2.5 4.5 1.7 Iris-virginica
108 7.3 2.9 6.3 1.8 Iris-virginica
109 6.7 2.5 5.8 1.8 Iris-virginica
110 7.2 3.6 6.1 2.5 Iris-virginica
111 6.5 3.2 5.1 2 Iris-virginica
112 6.4 2.7 5.3 1.9 Iris-virginica
113 6.8 3 5.5 2.1 Iris-virginica
114 5.7 2.5 5 2 Iris-virginica
115 5.8 2.8 5.1 2.4 Iris-virginica
116 6.4 3.2 5.3 2.3 Iris-virginica
117 6.5 3 5.5 1.8 Iris-virginica
118 7.7 3.8 6.7 2.2 Iris-virginica
119 7.7 2.6 6.9 2.3 Iris-virginica
120 6 2.2 5 1.5 Iris-virginica
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标题名称：TensorFlow如何读取CSV数据-创新互联
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