If you set plotly as your plotting backend for pandas, you can first group your data and do:
df.groupby(["state"]).count().reset_index().plot(x='state', y='value', kind='bar')
Complete snippet
import pandas as pd
pd.options.plotting.backend = "plotly"
df = pd.DataFrame({'id': {0: 19292, 1: 24592, 2: 12492, 3: 11022, 4: 99091, 5: 59820, 6: 50281},
'state': {0: 'CA', 1: 'CA', 2: 'GE', 3: 'GE', 4: 'CO', 5: 'CO', 6: 'CA'},
'value': {0: 100, 1: 200, 2: 340, 3: 500, 4: 250, 5: 220, 6: 900}})
df.groupby(["state"]).count().reset_index().plot(x='state', y='value', kind='bar')
But if you would like a setup that you can expand a bit more on, I would use px.bar like so:
dfg = df.groupby(["state"]).count()
fig = px.bar(dfg, x=dfg.index, y="value")
fig.show()
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