Why do seaborn.histplot and pyplot.hist generate two different histograms on the same data?

Question

I'm trying to visualize a customer data, two of the variables I'm looking at are verified_status and video_transcription_length.

• verified_status: the status of the videos, which contain verified and not verified
• video_transcription_length: the length of the video transcription

I'm trying to plot histograms to see if the distributions of video_transcription_length for verified and not verified videos are different or not.

If i use plt.hist, I get the following result

status_name = data_unsampled['verified_status'].unique() color=['red','green'] for i, status in enumerate(status_name): ax = data_unsampled[data_unsampled['verified_status']==status]['video_transcription_length'].hist(figsize=(8,4),bins=50, color=color[i]) ax.legend(status_name) ax.set_title('distribution of video_transcription_text length of 2 different video status') ax.set_xlabel('status') ax.set_ylabel('text length') plt.show() 

However if I use sns.histplot, I got a different result

sns.histplot(data=data_unsampled, stat="count", multiple="stack", x="video_transcription_length", kde=False, palette="pastel", hue="verified_status", element="bars", legend=True) plt.title("Seaborn Stacked Histogram") plt.xlabel("video_transcription_text length (number of characters)") plt.ylabel("Count") plt.title("Distribution of video_transcription_text length for videos posted by verified accounts and videos posted by unverified accounts") plt.show() 

Why does using seaborn and matplotlib get different results? And even in the second picture the not verified is much higher than verified, but in the first picture verified is higher than not verified.

What's the difference between these two?