Ways to convert textual data to numerical data I've been looking for ways to wrangle my data which contains both text and numerical attributes.

There are of course several algorithms for numerical data, but I am looking for suggestions regarding how to deal with textual data, for instance: for sorting based on K-means clustering and predicting missing data using kNN. I would really appreciate any thoughts regarding that. I am using scikit-learn.
A renown method is using two layers Neural Network which transform each word to a vector. you can use word2vec library also to do this. To know more about this you can find this online article useful.