Visualize data with tensorflow (tensorboard) embedding projector

visualize_data.py

#how-to: https://www.tensorflow.org/versions/r0.12/how_tos/embedding_viz/index.html
#run "tensorboard --log-path ../path/to/log" and open in browser
import tensorflow as tf
import os
import numpy as np

LOG_DIR='log'

def visualize_data(df):
    #Replace NaN with empty string
    df.fillna("", inplace=True)
    
    #Get labels from dataframe
    training_labels = df["label"].values
    df = df.drop("label",1)
    
    training_data = df.values
    
    #float input data
    input_var_data = tf.Variable(initial_value=training_data, dtype=np.dtype(float))
    #string input labels
    input_var_labels = tf.Variable(initial_value=training_labels)

    init_op = tf.global_variables_initializer()

    saver = tf.train.Saver()

    #create log dir
    if not os.path.exists(LOG_DIR):
        os.makedirs(LOG_DIR)

    #dummy session to save data as checkpoint
    with tf.Session() as sess:

        sess.run(init_op)

        for n in range(1):
            saver.save(sess, os.path.join(LOG_DIR, "model.ckpt"), n)



if __name__ == '__main__':
   #get dataframe
   visualize_data(dataframe)