End caps on barplot confidence intervals #606 update

[dcgemperline]

I think this fixes the end cap addition to barplot and scatterplot confidence intervals. Let me know what you think. It should pass all the automated tests. Let me know if there is anything wrong. I've attached some images, along with the python script I used to generate them. This should show you what the different parameters look like for different capsize and conf_lw. Major thanks to jat255 who did the initial work on this. This is my very first contribution to an open source project that is not my own. Let me know if there is anything else that needs to be done as far as style and/or code cleanup.

import seaborn as sns

##LINEPLOTS

g=None
sns.set(style="whitegrid")
df = sns.load_dataset("exercise")
g = sns.factorplot(x="time", y="pulse", hue="kind", col="diet", data=df,
                   palette="YlGnBu_d", size=6, aspect=.75)
g.despine(left=True)
g.savefig("test1.png")

g=None
sns.set(style="whitegrid")
df = sns.load_dataset("exercise")
g = sns.factorplot(x="time", y="pulse", hue="kind", col="diet", data=df,
                   palette="YlGnBu_d", size=6, aspect=.75, conf_lw=1, capsize=0.3)
g.despine(left=True)
g.savefig("test2.png")

g=None
sns.set(style="whitegrid")
df = sns.load_dataset("exercise")
g = sns.factorplot(x="time", y="pulse", hue="kind", col="diet", data=df,
                   palette="YlGnBu_d", size=6, aspect=.75, conf_lw=4, capsize=0.3)
g.despine(left=True)
g.savefig("test2b.png")

g=None
sns.set(style="whitegrid")
df = sns.load_dataset("exercise")
g = sns.factorplot(x="time", y="pulse", hue="kind", col="diet", data=df,
                   palette="YlGnBu_d", size=6, aspect=.75, conf_lw=1, capsize=0.1)
g.despine(left=True)
g.savefig("test3.png")

g=None
sns.set(style="whitegrid")
df = sns.load_dataset("exercise")
g = sns.factorplot(x="time", y="pulse", hue="kind", col="diet", data=df,
                   palette="YlGnBu_d", size=6, aspect=.75, conf_lw=2, capsize=0.3)
g.despine(left=True)
g.savefig("test4.png")

##BarPlots

g=None
sns.set(style="whitegrid")
titanic = sns.load_dataset("titanic")
g = sns.factorplot(x="class", y="survived", hue="sex", data=titanic,
                   size=6, kind="bar", palette="muted")
g.despine(left=True)
g.set_ylabels("survival probability")
g.savefig("test5.png")

g=None
sns.set(style="whitegrid")
titanic = sns.load_dataset("titanic")
g = sns.factorplot(x="class", y="survived", hue="sex", data=titanic,
                   size=6, kind="bar", palette="muted", conf_lw=1, capsize=0.3)
g.despine(left=True)
g.set_ylabels("survival probability")
g.savefig("test6.png")

g=None
sns.set(style="whitegrid")
titanic = sns.load_dataset("titanic")
g = sns.factorplot(x="class", y="survived", hue="sex", data=titanic,
                   size=6, kind="bar", palette="muted", conf_lw=1, capsize=0.1)
g.despine(left=True)
g.set_ylabels("survival probability")
g.savefig("test7.png")

g=None
sns.set(style="whitegrid")
titanic = sns.load_dataset("titanic")
g = sns.factorplot(x="class", y="survived", hue="sex", data=titanic,
                   size=6, kind="bar", palette="muted", conf_lw=2, capsize=0.3)
g.despine(left=True)
g.set_ylabels("survival probability")
g.savefig("test8.png")

`

[mwaskom]

Thanks for fixing the tests and getting this working in pointplot.

Please add some tests to cover this new behavior, though.

[mwaskom]

If you are testing against None, do so explicitly.

[mwaskom]

I have made some comments. I would suggest writing the tests first before addressing them so that you can guard against introducing errors when fixing.

[dcgemperline]

Thanks for the quick feedback. This is my first time really writing python, so I appreciate the code review. I will see if I can implement the tests, check them in and then work on getting the changes you suggested in as well.

[dcgemperline]

Python script with some values adjusting the errwidth and the capsize

`import seaborn as sns

##LINEPLOTS

g=None
sns.set(style="whitegrid")
df = sns.load_dataset("exercise")
g = sns.factorplot(x="time", y="pulse", hue="kind", col="diet", data=df,
palette="YlGnBu_d", size=6, aspect=.75)
g.despine(left=True)
g.savefig("test1.png")

g=None
sns.set(style="whitegrid")
df = sns.load_dataset("exercise")
g = sns.factorplot(x="time", y="pulse", hue="kind", col="diet", data=df,
palette="YlGnBu_d", size=6, aspect=.75, errwidth=1, capsize=0.3)
g.despine(left=True)
g.savefig("test2.png")

g=None
sns.set(style="whitegrid")
df = sns.load_dataset("exercise")
g = sns.factorplot(x="time", y="pulse", hue="kind", col="diet", data=df,
palette="YlGnBu_d", size=6, aspect=.75, errwidth=4, capsize=0.3)
g.despine(left=True)
g.savefig("test2b.png")

g=None
sns.set(style="whitegrid")
df = sns.load_dataset("exercise")
g = sns.factorplot(x="time", y="pulse", hue="kind", col="diet", data=df,
palette="YlGnBu_d", size=6, aspect=.75, errwidth=1, capsize=0.1)
g.despine(left=True)
g.savefig("test3.png")

g=None
sns.set(style="whitegrid")
df = sns.load_dataset("exercise")
g = sns.factorplot(x="time", y="pulse", hue="kind", col="diet", data=df,
palette="YlGnBu_d", size=6, aspect=.75, errwidth=2, capsize=0.3)
g.despine(left=True)
g.savefig("test4.png")

##BarPlots

g=None
sns.set(style="whitegrid")
titanic = sns.load_dataset("titanic")
g = sns.factorplot(x="class", y="survived", hue="sex", data=titanic,
size=6, kind="bar", palette="muted")
g.despine(left=True)
g.set_ylabels("survival probability")
g.savefig("test5.png")

g=None
sns.set(style="whitegrid")
titanic = sns.load_dataset("titanic")
g = sns.factorplot(x="class", y="survived", hue="sex", data=titanic,
size=6, kind="bar", palette="muted", errwidth=1, capsize=0.3)
g.despine(left=True)
g.set_ylabels("survival probability")
g.savefig("test6.png")

g=None
sns.set(style="whitegrid")
titanic = sns.load_dataset("titanic")
g = sns.factorplot(x="class", y="survived", hue="sex", data=titanic,
size=6, kind="bar", palette="muted", errwidth=1, capsize=0.1)
g.despine(left=True)
g.set_ylabels("survival probability")
g.savefig("test7.png")

g=None
sns.set(style="whitegrid")
titanic = sns.load_dataset("titanic")
g = sns.factorplot(x="class", y="survived", hue="sex", data=titanic,
size=6, kind="bar", palette="muted", errwidth=2, capsize=0.3)
g.despine(left=True)
g.set_ylabels("survival probability")
g.savefig("test8.png")
`

[dcgemperline]

I know you are quite busy, but does there need to be any more work done on this for it to be integrated?

[mwaskom]

On a very quick review the code looks clean and your example plots look very thorough, but I'm waiting to get the time to actually play with it myself for a bit before hitting merge. I'll ping you if it needs any more changes.

[mwaskom]

Thanks!

[dcgemperline]

No problem! Thanks for letting me contribute :)

[luthramanisha]

In seaborn version 0.9.0, new plotting functions including relplot() are released. These still don't have attributes err_width and cap_size for end caps in type line plots with confidence intervals.