Converting numpy array to tuple messes up the values inside

Question

some strange things are happening while I try to convert an numpy array to a tuple.

code:

data_block = np.append(training_values, target_value)  # merge
print('data_block: ', data_block)
data_block = tuple(data_block)
print('data_block tuple: ', data_block)

output:

data_block:  [ 0.03478261  0.00869565  0.03478261  0.07826087  0.05217391  0.07826087 0.14782609]
data_block tuple:  (0.034782608695652174, 0.0086956521739130436, 0.034782608695652174, 0.078260869565217397, 0.052173913043478258, 0.078260869565217397, 0.14782608695652172)

Can someone explain to me what is happening?

This is part of a function that tries to create data that can be used for supervised learning out of a time series. Goal is to create a pandas data frame. The function itself is not finished yet and contains errors, but I want to post it here for more context.

def series_to_supervised(data_list, look_back=1, look_forward=0):
print(look_back)
data, labels = [], []
for i in range(len(data_list) - look_back):
    training_values = data_list[i:(i + look_back)]  
    target_value = data_list[i + look_back + look_forward]  
    print('target_value: ', target_value)

    data_block = np.append(training_values, target_value)  # merge
    data_block = tuple(data_block)
    data = np.append(data, data_block)  # add to data as tuple

for i in range(look_back):
    labels.append("lb_" + str(i))
labels.append("target_value")
print(labels)

df = pandas.DataFrame(data=data)
return df

The values are not "messed up", they are just printed at a higher precision (more digits after the comma). — xdurch0
– xdurch0, Commented Dec 19, 2018 at 12:43

tel · Accepted Answer · 2018-12-19 12:49:07Z

1

The values that you show for data_block and tuple(data_block) actually do match. Numpy arrays get printed a little differently from most other things in Python, so the output of the print statements looks a little different.

You can get the printed output to match like so:

with np.printoptions(precision=20, linewidth=9999):
    print(data_block)
print(tuple(data_block))

Output:

[0.034782608695652174 0.008695652173913044 0.034782608695652174 0.0782608695652174   0.05217391304347826  0.0782608695652174   0.14782608695652172 ]
(0.034782608695652174, 0.008695652173913044, 0.034782608695652174, 0.0782608695652174, 0.05217391304347826, 0.0782608695652174, 0.14782608695652172)

If you always want your numpy arrays to print at that high precision (which you probably don't in reality; it gets annoying quickly), you can set a global option in your script like so:

np.set_printoptions(precision=20)

edited Dec 19, 2018 at 12:49

answered Dec 19, 2018 at 12:41

tel

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2 Comments

Wikktor Over a year ago

Aaahhh sry for that. Never thougt about that and it confused me. Many thanks and sorry for the stupid question :_(

tel Over a year ago

floats are some damn mysterious objects when you're just starting out. No worries.

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