Tag: data-mining

Python : y should be a 1d array, got an array of shape {} instead. format(shape)

classification data-mining python regression

The above is my code which I tried in Google Colab. But here it shows one error : This is error is shown in the line Please help me to solve this error. I am a beginner so answer the question with elaboration Answer Your problem is that the outputs of train_test_split are ordered differently than you think. train_test_split returns

Finding string with multiple condition between two data frame in python

data-mining dataframe pandas python string

I have two dataframe df1 and df2. df1 has 4 columns. I want to add a new column Count in df2 in such a way that for every row in df2 if any string from Intersection or Roadway column exists in overall df1 data frame even once or more, the count column will have a value of 1. For example

Verify that a column name is a unique identifier

data-mining pandas python

I have a dataset called df_authors and in that dataset I have a column called author. I have to verify that df_authors.author is a unique identifier. What I tried, len(df_authors) == len(df_authors[‘author’].unique()), and this returns True. My question is have I done this right. I found this line of code online and not a 100% sure if it does what

sklearn Clustering: Fastest way to determine optimal number of cluster on large data sets

bigdata cluster-analysis data-mining python scikit-learn

I use KMeans and the silhouette_score from sklearn in python to calculate my cluster, but on >10.000 samples with >1000 cluster calculating the silhouette_score is very slow. Is there a faster method to determine the optimal number of cluster? Or should I change the clustering algorithm? If yes, which is the best (and fastest) algorithm for a data set with