I would like to use pandas to prepare an array from a CSV file to then use in keras.
Here is an example of load_data() that I have, which works:
import tensorflow as tf
mnist = tf.keras.datasets.mnist
(x_train, y_train), (x_test, y_test) = mnist.load_data()
Here is my attempt to load my own array using read_csv() (1530 rows with 42 columns, first col string, rest numbers (some int, most float)):
import pandas as pd
training_data = pd.read_csv('fName.csv',index_col='ID')
Both snippes work fine, but read_csv() does not let me access the content. While the first version with load_data() allows to access the actual array content, the array training_data that I read with read_csv() gives the error below:
>>> x_train[1,10,10:20]
array([238, 252, 252, 179, 12, 75, 121, 21, 0, 0], dtype=uint8)
>>> training_data[1,10:20]
TypeError: '(1, slice(10, 20, None))' is an invalid key
Both arrays seam to read properly - so what am I not doing right?
>>> np.ndim(x_train)
3
>>> np.ndim(training_data)
2
What can I do?