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Tag: numpy

scipy.stats.cumfreq() isn’t the cumulative frequency I’m looking for

Reading a statistic book, I’m also training with Python. My book asks me to calculate the cumulative workforce and the cumulative frequency of a simple list of jobs. Secteur Nombre d’emplois Agriculture 21143585 Construction 35197834 Industrie 69941779 Fabrication 64298386 Services 368931820 I wrote this Python program: that responds me: And if my book agrees for the cumulative workforce, it doesn’t

How to plot hour:min time in ISO 8601 time format?

I am trying to plot temperature data points according to their time recording. Note: as you have mentioned t is represented without hour, the reason is that temp been collected in hour:second. t is a string representing the date and time in ISO 8601 format (ref: datetime.datetime.isoformat()) and temp is a floating number. The plot should be in a way

Numpy rounding issue

Can someone explain to me why is numpy round acting strange with this exact number rounding: It’s obvious that the first number is not rounded well, any ideas? EDIT: Since I’m focused here on the precision, not so much on the performance, I’ve used python round function to solve this problem: Answer Check the small print 2 in the documentation

Remove specific rows that contain dates Python

I have a dataset that has datetime values in it. I would like to remove all rows within a specific column that contain a certain year. All rows that contain 2027 should be removed. Data Desired Doing Any suggestion is appreciated. Error: AttributeError: Can only use .str accessor with string values! I believe I need to do some type of

layer.get_weights() is not equal in the same model layers

Why not all the layer weights equal: Here is the output: The a_weights == b_weights are not all the “True”. What’s the problem? Answer Notice that the only time a_weights == b_weights is True, is when you are referencing a layer, which does not have any weights. np.array_equal is returning False because you are actually comparing lists of arrays and

How to fill in missing center of a 2d gaussian

I have a 2d gaussian whose center has been destroyed by pixel saturation. I need the center to be filled in because a poorly filled in center will confuse a neural network I’m trying to train. See below: The scattered nan values I can handle fairly easily, but the large cluster in the gaussian’s center I cannot. I’ve tried various

convert multiple units to KG in pandas

let’s say i have this code(which is obviously wrong) I want to apply such condition to each value in a column(weights) based on another column(weight unit). Is there an efficient way to do it. Preferably allowing a func pass so easy to modify Answer Don’t use a function, this will be slow. numpy.vectorize does not vectorize in C-speed, but rather

Reordering a list based on another list in Python

I have two lists Ii0 and Iv0 containing numpy arrays. I am using argsort() to reorder elements in Ii0 to generate a new list Ii01. I want to use the same order to reorder elements in Iv0 to generate a new list Iv01. I present the current and expected output. The current output is The expected output is Answer Use:

Is there a way to resize a batch of images?

I am trying to make code of object detection efficient. I currently have multiple sources, Below is the pseudo code: Take images via cv2.imread() or cap.read() from all sources one by one. Pre-process them one by one: a. Resize b. Normalise Make batch. Pass to model. Post process one by one. Now, since images read my opencv are nothing just

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