data-science

问题 I have a pandas data frame that contains information about messages sent by user. For my model, I'm interested in predicting missing recipients of a message i,e given recipients A,B,C of a message I want to predict who else should have been part of the recipients. I'm doing multi-label classification using OneVsRestClassifier and LinearSVC. For features, I want to use the recipients of the message. subject and body. Since recipients is a list of users, I want to transform that column using

问题 I have a pandas data frame that contains information about messages sent by user. For my model, I'm interested in predicting missing recipients of a message i,e given recipients A,B,C of a message I want to predict who else should have been part of the recipients. I'm doing multi-label classification using OneVsRestClassifier and LinearSVC. For features, I want to use the recipients of the message. subject and body. Since recipients is a list of users, I want to transform that column using

问题 I need to know whether coherence score of 0.4 is good or bad? I use LDA as topic modelling algorithm. What is the average coherence score in this context. 回答1: Coherence measures the relative distance between words within a topic. There are two major types C_V typically 0 < x < 1 and uMass -14 < x < 14. It's rare to see a coherence of 1 or +.9 unless the words being measured are either identical words or bigrams. Like United and States would likely return a coherence score of ~.94 or hero and

问题 Getting started with Pandas. I have two columns: A B Something Something Else Everything Evythn Someone Cat Everyone Evr1 I want to calculate fuzz ratio for each row between the two columns so the output would be something like this: A B Ratio Something Something Else 12 Everything Evythn 14 Someone Cat 10 Everyone Evr1 20 How would I be able to accomplish this? Both the columns are in the same df. 回答1: Use lambda function with DataFrame.apply: from fuzzywuzzy import fuzz df['Ratio'] = df

问题 I downloaded the BraTS dataset for my summer project. The dataset consisted of nii.gz files which I was able to open using nibabel library in Python. I used the following code: import os import numpy as np import nibabel as nib import matplotlib.pyplot as plat examplefile=os.path.join("mydatapath","BraTS19_2013_5_1_flair.nii.gz") img=nib.load(examplefile) print(img) this gave me the following output: <class 'nibabel.nifti1.Nifti1Image'> data shape (240, 240, 155) affine: [[ -1. 0. 0. -0.] [ 0

问题 This is the data in single cell of dataframe with 14 columns. Cell is the element of column. There are 45k+ this kind of cells, to do it manually is a hell. one cell data I'd like to do with this cell 3 things: move text part with address, state, zip - to another column; delete the hooks () of cell; separate for 2 columns longitude and latitude. How it's possible to do? 回答1: Here's a simple, working example with 2 data points: text1 = """30881 EKLUTNA LAKE RD CHUGIAK, AK 99567 (61.4478, -149

问题 This is the data in single cell of dataframe with 14 columns. Cell is the element of column. There are 45k+ this kind of cells, to do it manually is a hell. one cell data I'd like to do with this cell 3 things: move text part with address, state, zip - to another column; delete the hooks () of cell; separate for 2 columns longitude and latitude. How it's possible to do? 回答1: Here's a simple, working example with 2 data points: text1 = """30881 EKLUTNA LAKE RD CHUGIAK, AK 99567 (61.4478, -149

问题 When I am trying to generate report using pandas profiling , I am getting below error while using below code: KeyError: 'script_values' import pandas_profiling from pandas_profiling import ProfileReport report = ProfileReport(df) report Can you please let me know why I am getting 'script_values' error. I googled all around but not able to find a solution. 回答1: There was a compatibility issue with one of the dependencies. A fix has been released. Your problem should be resolved by updating to

问题 I put together the following function that read csv, train the model and predict the request data. I've got the following ValueError : Column ordering must be equal for fit and for transform when using the remainder keyword The training data and the data used for prediction has exact the same number of column , e.g., 15. I am not sure how the "ordering" of the column could have changed. ~/.local/lib/python3.5/site-packages/sklearn/pipeline.py in predict(self, X, **predict_params) 417 Xt = X

问题 I am trying to read rds file, directly from GitHub. I am able to read any file from git but when I try to read rds file using gzcon its asking value for con. dat <- readRDS(gzcon(url("http://mgimond.github.io/ES218/Data/ABC.rds"))) exception : con has not defined. what type of connection it requires? 回答1: If you are having issues one way is to download the file as a tempfile. url <- "mgimond.github.io/ES218/Data/ACS.rds" temp <- tempfile() # create a tempfile download.file(url, temp) #