I have CSV file with Vector3 values exported from a C# program. I would like to use vector operations (like calculating the distance etc.) in pandas. As far as I have seen, there is no Vector3 type in pandas. np.array offers this kind of operations but it is not available in pandas. What is the easiest way to accomplish vector
Tag: numpy
The most efficient way rather than using np.setdiff1d and np.in1d, to remove common values of 1D arrays with unique values
I need a much faster code to remove values of an 1D array (array length ~ 10-15) that are common with another 1D array (array length ~ 1e5-5e5 –> rarely up to 7e5), which are index arrays contain integers. There is no duplicate in the arrays, and they are not sorted and the order of the values must be kept
How to increase the size of only one plot in subplots?
If you have two subplots, how do you change the length of only the second plot? Adding figsize=(7,5) to plt.subplots changes the size of both plots, but hoping to change only the size of the 2nd one. source code: https://www.w3schools.com/python/matplotlib_subplot.asp There are no errors, but how do you adjust the size of only the 2nd plot but keeping the placement
How to change data type in a list of tuples if this type is Timestamp?
I have a list of tuples like this: What I do is: How can I do to change directly the Timestamp type in this list of tuples ? More precisely, if type is pd.Timestamp I would like to change it to np.datetime64. Answer This is an example that should explain what you are missing. The result: [[’12’, 123, ‘test_1′], [’14’,
psycopg update with unnest for a bytea column
I’m trying to update a lot of row in my database using unnest(). Here’s my db: Then I update the table with: But I got the following error: However, it’s working if I do a classic update. Any idea ? Answer Since your data is a 2×100 matrix, is better to partition it in vectors (1d array) for each parameter
Output sum rounded to the nearest even number using Python
I wish to take the sum of each row and round this value to the closest even number. Data Desired Doing I realize I have to incorporate i+i.mod(2) into this script, however I am not sure how to incorporate. Any suggestion is helpful. Answer here is one way to do it
How can I extract values from a 3D numpy array using a 2D numpy array with indices?
I have two numpy arrays of the following shapes, and I need to extract values from a 3D array using stored indices from a 2D one: vals = (65, 65, 3500) This contains 3500 values that were calculated in a 65×65 grid, from which I need to extract values indices = (65, 65) This contains the indices of the minimum
Can I sort two related arrays in parallel using python?
I have two NumPy arrays with the shape (74395, 1) storing float values where arr1[0] correlates to arr2[0] and so on. I would like to sort them together in ascending order by the values stored in the second array. As an example: wanted result: How could I do that in python? Answer Use numpy.argsort with numpy.take_along_axis: Output:
Column as a sum of its cumulative value only if other column meets condition
I am struggling to produce below df[‘res’] without loop / within pandas. Loop implementation of df[‘res’] In pandas, it could be something like The issue is that df[‘res’] is previously empty. Any hint how to think about these decompositions? Answer As per your requirement, the value for temp will be reset as soon as we reach a 0 in a.
How to assign values to multiple columns using conditions for values from other multiple columns?
Dataset is something like this (there will be duplicate rows in the original): Code: Output should be this: Code: ‘series1′ column values starts row by row as 0, 1, 2, and so on but resets to 0 when: ’email_ID’ column value changes. ‘screen’ column value == ‘rewardapp.PaymentFinalConfirmationActivity’ ‘series2’ column values starts with 0 and increments by 1 whenever ‘series1’ resets.