How to plot word frequency, from a column of lists, in a bar chart

I have dataframe

I am struggling to show the top 10 words in a bar chart for all tweets, real tweets and fake. Any suggestions?

Divide all texts into words, count the frequencies, select the 10 most frequent ones and plot them. I thought something like this could work but as a novice I'm unsure how to implement this.

Solution

The primary requirement is to use pandas.Series.explode to separate all the values in a list to separate rows.
.groupby and aggregate .count on the values in the column, and then .sort_values
Use pandas.DataFrame.plot.bar to plot the words

import pandas as pd
import matplotlib.pyplot as plt

# test dataframe
df = pd.DataFrame({'lemmatized': [['se', 'acuerdan', 'de', 'la', 'pelicula el', 'dia'], ['milenagimon', 'miren', 'sandy', 'en', 'ny', 'tremenda'], ['se', 'acuerdan', 'de']]})

# display(df)
                                      lemmatized
0       [se, acuerdan, de, la, pelicula el, dia]
1  [milenagimon, miren, sandy, en, ny, tremenda]
2                             [se, acuerdan, de]

# use explode to expand the lists into separate rows
dfe = df.lemmatized.explode().to_frame().reset_index(drop=True)

# groupby the values in the column, get the count and sort
dfg = dfe.groupby('lemmatized').lemmatized.count() \
                               .reset_index(name='count') \
                               .sort_values(['count'], ascending=False) \
                               .head(10).reset_index(drop=True)

# display(dfg)
    lemmatized  count
0     acuerdan      2
1           de      2
2           se      2
3          dia      1
4           en      1
5           la      1
6  milenagimon      1
7        miren      1
8           ny      1
9  pelicula el      1

# plot the dataframe
dfg.plot.bar(x='lemmatized')

Alternative Implementations

Use .value_counts instead of .groupby

# use value_counts and plot the series
dfe.lemmatized.value_counts().head(10).plot.bar()

Using seaborn.countplot

import seaborn as sns

# plot dfe
sns.countplot(x='lemmatized', data=dfe, order=dfe.lemmatized.value_counts().iloc[:10].index)
plt.xticks(rotation=90)