How to *actually* read CSV data in TensorFlow?

Question

I\'m relatively new to the world of TensorFlow, and pretty perplexed by how you\'d actually read CSV data into a usable example/label tensors in Te

Answer 1

Or you could try this, the code loads the Iris dataset into tensorflow using pandas and numpy and a simple one neuron output is printed in the session. Hope it helps for a basic understanding.... [ I havent added the way of one hot decoding labels].

import tensorflow as tf 
import numpy
import pandas as pd
df=pd.read_csv('/home/nagarjun/Desktop/Iris.csv',usecols = [0,1,2,3,4],skiprows = [0],header=None)
d = df.values
l = pd.read_csv('/home/nagarjun/Desktop/Iris.csv',usecols = [5] ,header=None)
labels = l.values
data = numpy.float32(d)
labels = numpy.array(l,'str')
#print data, labels

#tensorflow
x = tf.placeholder(tf.float32,shape=(150,5))
x = data
w = tf.random_normal([100,150],mean=0.0, stddev=1.0, dtype=tf.float32)
y = tf.nn.softmax(tf.matmul(w,x))

with tf.Session() as sess:
    print sess.run(y)