FAQ: The Data Science Process - Communicating Findings

This community-built FAQ covers the “Communicating Findings” exercise from the lesson “The Data Science Process”.

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FAQs on the exercise Communicating Findings

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What happened to the population numbers 100K, 1M, 2M, 4M and 8M in the second and third graphs? Why did it go back to 0.0, 0.2, 0.4, 0.6 and 0.8?

5 Likes

Same thing happened here.
Also the labels in the last table don’t change for Population (ax.set_xlabel(“City Population”)) and Age
(ax.set_ylabel(“User Age”)).

Does anyone know why?
Thanks in advance

1 Like

Hello! This seemed to work better for me.

Paste code to change the figure style and palette:

plt.close()

sns.set_style(“darkgrid”)
sns.set_palette(“bright”)
sns.despine()

sns.regplot(x=“population_proper”, y=“age”, data=new_df)
ax = plt.subplot(1, 1, 1)
ax.set_xticks([100000, 1000000, 2000000, 4000000, 8000000])
ax.set_xticklabels([“100k”, “1m”, “2m”,“4m”, “8m”])
plt.show()

Paste code to title the axes and the plot:

plt.close()

sns.regplot(x=“population_proper”, y=“age”, data=new_df)
ax = plt.subplot(1, 1, 1)
ax.set_xticks([100000, 1000000, 2000000, 4000000, 8000000])
ax.set_xticklabels([“100k”, “1m”, “2m”,“4m”, “8m”])

ax.set_xlabel(“City Population”)
ax.set_ylabel(“User Age”)
plt.title(“Age vs Population”)

plt.show()

1 Like