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Seaborn factor plot with transformation

I am trying to plot a factor’s data. On my factor, I have a range of values from 0.2 to 1 and I want to plot the y values in a range of 0.2 to 1. I tried doing it with a transformation but I am getting different plots. This is what I have so far:
data = pd.DataFrame(np.random.randint(1,4,size=(20,20))).values
data = np.array(data).reshape(-1,1)
labels = data.astype(str)

#here the labels with 0.2 to 1 I want to take their max values.
labels1 = np.array(labels[labels>0.2].argmax())[0]

# here I want to plot 0.2 to 1 with different x values.
fig, ax = plt.subplots()
ax.plot(labels1, data)

This is what I got:

When I do this:
labels1 = np.array(labels[labels>0.2].max()).reshape(-1,1)
ax.plot(labels1, data)

I get this:

A:

As your labels range from 0.2 to 1, this should work:
# replace the max() with min() if labels.min() == 0
plt.subplot(111)
plt.xlabel(‘Label’)
plt.ylabel(‘Data’)
plt.tick_params(axis=’both’, which=’major’, labelsize=14)
plt.title(‘Factor Graph Plot’)
plt.tight_layout()

plt.bar(range(0.2

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