As what I can understand from your example, this maybe a solution, replace value_counts
by count
.
Example data:
import pandas as pd
import matplotlib.pyplot as plt
df = pd.DataFrame({'Year': [ 2019, 2019, 2020, 2021], 'Product_Category': ['a', 'b', 'c', 'd']})
print(df)
Year Product_Category
0 2019 a
1 2019 b
2 2020 c
3 2021 d
The count will return:
plot1 = df.groupby('Year')['Product_Category'].count().rename('count').reset_index()
print(plot1)
Year count
0 2019 2
1 2020 1
2 2021 1
plot1 = df.groupby('Year')['Product_Category'].count().rename('count').reset_index()
#x,y#
x = plot1['Year'].values.reshape(-1, 1)
y = plot1['count'].values.reshape(-1, 1)
# plot #
#plot#
plt.scatter(x, y, color='black')
plt.plot(x, y, color='blue', linewidth=3)
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