I am looking to plot monthly air quality data in a Seaborn lineplot. As the months with the worst air quality are Nov-Feb, I would like to have these months in the middle of the lineplot. My question is, can this be done?
concentration vs month
axes[1] = sns.lineplot(ax=axes[1],
data=df_month,
#x=df['date'],
x=df_month['month'],
y=df_month['monthly mean'],
color='red',
linewidth=1.5,
#hue=hue,
palette="hls")
This is the plot that is currently being produced
I tried to order the month values categorically but this returned a blank chart
df_month['month'] = pd.Categorical(df_month['month'],
categories=['6', '7', '8', '9', '10', '11', '12', '1',
'2', '3', '4', '5'],
ordered=True)
This is the data I am trying to plot
location month monthly mean
1 Location A 3 87.98375
2 Location A 4 45.91740741
3 Location A 5 21.71923077
4 Location A 6 12.84966667
5 Location A 7 10.09612903
6 Location A 8 13.80387097
7 Location A 9 18.598
8 Location A 10 37.799
9 Location A 11 108.124
10 Location A 12 71.87241379
11 Location A 1 138.5916129
12 Location A 2 55.36103448
This is an excel graph of what I am trying to achieve
Thanks for your help @JohanC. I did not realise that I had to sort the values after applying pd.Categorical. (I also realised I was incorrectly putting the month numbers in quotation marks)
# set categorical order
df_month['month'] = pd.Categorical(df_month['month'], categories=[6, 7, 8, 9,
10, 11, 12, 1, 2, 3, 4, 5], ordered=True)
df_month.sort_values('month', inplace=True)
Once I did that, I could use your helpful suggestion of sns.pointplot to achieve the chart I was aiming for.
# concentration vs month
axes[1] = sns.pointplot(ax=axes[1],
data=df_month,
x='month',
y='monthly max mean',
color='red',
scale =0.6,
markers='',
order=df_month['month'])
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