I am trying to modify my print statement within the for loop below so that it iterates through the list and the dictionary and prints the values of the first and second numpy arrays. In accordance to the Timeframes list. How can I modify the print statement below to get the Expected output below? Expected Output: Answer If you make
Tag: numpy
Numpy matrix creation timing oddity
My application requires a starting matrix where each column is staggered-by-1 from the previous. It will contain millions of complex numbers representing a signal, but a small example is: I tried two creation methods, one fast, one slow. I don’t understand why the fast matrix creation method causes subsequent calculations to run slowly, while the slow matrix creation results in
Assigning keys and storing in a dictionary Python
For an event of rolling a six-sided die. I need to randomly simulate the event 1000 times and plot a histogram of results for each number on the dice. I want to assign the results for each number to a key of the same value (1 for number of 1s{1:164…}). I need help assigning keys and storing everyting in a
Pandas: efficiently inserting a large number of rows
I have a large dataframe in this format, call this df: index val1 val2 0 0.2 0.1 1 0.5 0.7 2 0.3 0.4 I have a row I will be inserting, call this myrow: index val1 val2 -1 0.9 0.9 I wish to insert this row 3 times after every row in the original dataframe, i.e.: index val1 val2 0
ndpointer in ctypes structure field
I cannot figure out how to use numpy.ndpointer as a field in a python ctypes structure. Here is some basic code, showing how I can do this without using ndpointer, but I would like to know if it’s possible to use ndpointer as well if it’s possible! Using the above code this works fine But when I call this, I
Python Pandas Dataframe enrichment (from another)
I would like to enrich a dataframe (df1) from another(df2) by adding a new column in df1 and enriching it based on what I find in df2. The size of the 2 df is different as well as the name of the columns. I would like to do like a Vlookup function in Excel. This what I’ve done but I
Read datasets one by one and put them next to the previous plot
I have some datasets which are too big and I want to plot these datasets with matplotlib’s imshow() function. I need to plot the datasets concatenated with matplotlib, but since the datasets are quite large, when I try to concatenate it causes my computer to overheat (I use the NumPy library to concatenate). Is it possible for me to read
Looking for a more efficient way to do the array multiplication in this loop
I have a script that is taking a bit long to run, so I was trying to look through and speed it up where I can. I found a part that takes ~10 minutes or so and I feel like it could be a bit more efficient, but I might be wrong. Basically, I am trying to multiply one array,
String modification and sampling change
i have this table: ID points values (x1;y1|x2;y2|x3;y3|x4;y4……….) 1 8 0,5;1|1;1,5|4;6|5;7|6;9|8;10|10;12|15;18 2 4 20;30|21;32|22;36|25;37 3 306 1;2|3;6|7;9|10;17|11;18|13;22|14;25|19;26|.. the points determine the number of points. It means for example – 306 (306 x points and 306 y points) My overall goal is to change the sampling density (the start and end points remain) – when i have 8 points, i want
Compare two arrays and print out Index of row in python
I have two arrays A and B I want to compare a couple of the elements of A[:,2:4] with couple elements of B[:,2:4] and print out the rows where they are equal or approximate? Here is my approach just for only A[:,3] How can I do it with both A[:,2] and A[:,3] ? Many thanks Answer I think you are