I found in SO an explanation to add a legend to this type of graph. However, it does not translate well with my data. I got my graph with circles and shades of colors to work. I do have the legend indicating what the shades of color mean in terms of ratio of users abandoning a chatbot at a given
Tag: python
python – check presence of predefined color ranges in image
I would need to verify if and how much of certain predefined color ranges are present in a image file. each color range is defined by 6 variables and a counter in a colorRange class: The image can either be a file, or loaded from the camera. Following code loads the image from the camera buffer: what I would …
What is the equivalent of connecting to google cloud storage(gcs) like in aws s3 using s3fs?
I want to access google cloud storage as in the code below. Answer You’re looking for gcsfs. Both s3fs and gcsfs are part of the fsspec project and have very similar APIs. Note that both of these can be accessed from the fsspec interface, as long as you have the underlying drivers installed, e.g.: fsspe…
Why does multiplying audio signal amplitude by any coefficient doesn’t change it?
Suppose you have the following float32 audio representation loaded from any wav file using the librosa package: If you then will try to play this audio using, for example, a jupyter notebook, the following snippets sounds in the same way: Why does it happen that changing audio aptitude (if I correctly underst…
make function memory efficent or store data somewhere else to avoid memory error
I currently have a for loop which is finding and storing combinations in a list. The possible combinations are very large and I need to be able to access the combos. can I use an empty relational db like SQLite to store my list on a disk instead of using list = []? Essentially what I am asking is whether
problem with pd.wide_to_long specifications
I have a dataframe that looks like the following: id xx_04-Feb-94 yyy_04-Feb-94 z_04-Feb-94 xx_22-Mar-94 yyy_22-Mar-94 z_22-Mar-94 123 456 789 with values inside the table filled out. I would like to pivot the data from wide to long. the desired output looks as follows: id date xx yyy z 123 04-Feb-94 123 22-M…
Tensorflow: `tf.reshape((), (0))` works fine in eager mode but ValueError in Graph mode
As the title, the function tf.reshape((), (0)) works perfectly fine in eager mode. But when I use it in Graph mode, it returns: ValueError: Shape must be rank 1 but is rank 0 for ‘{{node Reshape}} = Reshape[T=DT_FLOAT, Tshape=DT_INT32](Reshape/tensor, Reshape/shape)’ with input shapes: [0], []. Ca…
Calculate column value count as a bar plot in Python dataframe
I have time series data and want to see total number of Septic (1) and Non-septic (0) patients in the SepsisLabel column. The Non-septic patients don’t have entries of ‘1’. While the Septic patients have first ‘Zeros (0)’ then it changes to ‘1’ means it now becomes se…
Loop through files in folder, read and group files
I am trying to read a csv file, resample it and save it with a different name So far I got this: But I get an error due to syntax being wrong, any ideas? Answer One error I could see is that you use backslashes (“”) in your path. The backslash serves as escape character in python strings which mea…
Caching a PySpark Dataframe
Suppose we have a PySpark dataframe df with ~10M rows. Also let the columns be [col_a, col_b]. Which would be faster: or Would caching df_test make sense here? Answer It won’t make much difference. it is just one loop where you can skip cache like below Here spark is loading Data once in memory. If you …