<jupyter_start><jupyter_text>**test**<jupyter_code>import plotly.plotly as plot
import pandas as pd<jupyter_output><empty_output><jupyter_text>Make some fake expression data<jupyter_code>expression = [
    {"name" : "head", "expr" : -1},
    {"name" : "shoulders", "expr" : 2},
    {"name" : "knees", "expr" : 4},
    {"name" : "toes", "expr": -2}]<jupyter_output><empty_output><jupyter_text>Pop it in a dataframe<jupyter_code>df = pd.DataFrame(data=expression)<jupyter_output><empty_output><jupyter_text>Let's see what the dataframe looks like...<jupyter_code>df<jupyter_output><empty_output><jupyter_text>Ok, let's try to put this in a chart.<jupyter_code>from plotly.graph_objs import *

data = [Bar(x=df.name,
            y=df.expr)]

plot.iplot(data, filename='basic_bar')<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.161090458488228, 'fraction_numerical': 0.004956629491945477, 'mean_word_length': 6.481481481481482, 'pattern_counts': {'":': 1, '<': 21, '<?xml version=': 0, '>': 21, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '5', 'dir': 'jupyter-structured-clean-dedup', 'id': '172773', 'license': 'MIT', 'n_tokens_mistral': 323, 'n_tokens_neox': 316, 'n_words': 54, 'path': 'Playing with a bar chart on plotly.ipynb', 'repo_name': 'yochannah/teaching-myself-python', 'size': '807'}