[{'role': 'system', 'content': "You are an expert in machine learning and your task is to classify the code snippets into categories from the provided list of categories. List of categories: ['helper_functions', 'load_data', 'data_exploration', 'data_preprocessing', 'evaluation', 'modelling', 'prediction', 'result_visualization', 'save_results', 'comment_only']"}, {'role': 'user', 'content': 'Identify to which category the provided code belongs and assign the code snippet to at least 1 but up to 5 categories based on the probabilities, ignore if the probability of the category is negligible. Strictly provide your response as a list. Avoid providing any additional information, commentary, or personal opinions.\\nPython Code:import plotly.plotly as plty\nplty.sign_in(\'cxu2\', \'zbb3igol1b\')\nfor col in rd.columns:\nrd[col] = rd[col].astype(str)\nscl = [[0.0, \'rgb(242,240,247)\'],[0.2, \'rgb(218,218,235)\'],[0.4, \'rgb(188,189,220)\'],\\\n[0.6, \'rgb(158,154,200)\'],[0.8, \'rgb(117,107,177)\'],[1.0, \'rgb(84,39,143)\']]\nrd[\'text\'] = rd[\'state\'] + \'<br>\'\ndata2 = [ dict(\ntype=\'choropleth\',\ncolorscale = scl,\nautocolorscale = False,\nlocations = rd[\'state\'],\nz = rd[\'rate\'].astype(float),\nlocationmode = \'USA-states\',\ntext = rd[\'text\'],\nmarker = dict(\nline = dict (\ncolor = \'rgb(255,255,255)\',\nwidth = 2\n) ),\ncolorbar = dict(\ntitle = "Rate of reviews")\n) ]\nlayout = dict(\ntitle = \'Movie Review Amount/Population among Different States\',\ngeo = dict(\nscope=\'usa\',\nprojection=dict( type=\'albers usa\' ),\nshowlakes = True,\nlakecolor = \'rgb(255, 255, 255)\'),\n)\nfig = dict( data=data2, layout=layout )\nplty.iplot( fig, filename=\'d3-cloropleth-map\' )'}, {'role': 'assistant', 'content': "['helper_functions', 'data_exploration']"}]