WordCloud | 一个用python写的词云生成器 -

As the title clearly describes the issue I've been experiencing, no Pipfile.lock is being generated as I get the following error when I execute the recommended command pipenv lock --clear:

I want to create a wordcloud where each line is displayed based on its count/frequency. The wordcloud should not be based on single words but on each sentence. The issue is that if I use wordcloud2, it does not display longer sentences and omits 2 of such sentences from the sample. How can I view all the sentences? Below is a dummy dataset similar to original:

Getting below validation error on opening my notebook :

{ "metadata": { "trusted": true }, "id": "comparative-import", "cell_type": "code", "source": "import numpy as np\nimport pandas as pd\nimport matplotlib.pyplot as plt\nimport seaborn as sns\nimport nltk\nimport re\nimport gensim \nfrom gensim.utils import simple_preprocess\nfrom gensim.models.word2vec import Word2Vec\nfrom nltk.stem.porter import PorterStemmer\nfrom nltk.corpus import stopwords\nfrom sklearn.decomposition import PCA,TruncatedSVD\nfrom sklearn.manifold import TSNE\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.linear_model import LogisticRegression\nfrom wordcloud import WordCloud, STOPWORDS, ImageColorGenerator\n", "execution_count": 10, "outputs": [] }

I have this small function that is not doing what I want it to do, and I am not sure why. The function is supposed to add the new_text string to the text list in the wordclouds dictionary.

I am trying to visualise data using word cloud however when I used pip install wordcloud I get the following error:

I ran into an issue using the unnest_tokens function on a data_frame. I am working with pdf files I want to compare.

To speed up my cluster instantiation time, I've created a custom image with all the additional dependencies installed using miniconda3 available for dataproc image 1.5.34-debian10. (I followed the steps here: GCP Dataproc custom image Python environment to ensure I used the correct python environment).

However, when I start my cluster with --optional-components ANACONDA,JUPYTER my custom dependencies are removed and I'm left with a base installation of anaconda and jupyter. I assume the anaconda installation is overwriting my custom dependencies. Is there any way to ensure my dependencies aren't overwritten? If not, is it possible to install anaconda and jupyter as part of my custom dataproc image instead?

I've used the following command to create the custom image:

I am just learning to code using the wordcloud and stylecloud libraries in python 3.9.0. I wrote the basic code for the stylecloud library but it gives an error that says:

ImportError: cannot import name 'makeMappingArray' from 'matplotlib.colors'

This is the code:

I am currently trying to save a word cloud I am generating in my AWS lambda function to my s3 bucket, my code executes gut gives "errorMessage": "Parameter validation failed:\nInvalid type for parameter Body, value: , type: , valid types: , , file-like object",

as an error, I have looked online and cant seem to find the cause, do I need to to convert the plot to bytes to be able to store it in S3 like this?