如何从我的时间序列数据中提取年份的 label 我的 x 轴？

Question

I have data in this format / shape etc in a dataframe that I would like to represent in the form of a graph showing the total counts per each month. I have resampled the data so that it shows one row for one month, and then I wrote the following code to chart it out:

import seaborn as sns
import pandas as pd
import matplotlib.pyplot as plt

#Read in data & create total column
stacked_bar_data = new_df
stacked_bar_data["total"] = stacked_bar_data.var1 + stacked_bar_data.var2

#Set general plot properties
sns.set_style("whitegrid")
sns.set_context({"figure.figsize": (24, 10)})
sns.set_context("poster")

#Plot 1 - background - "total" (top) series
sns.barplot(x = stacked_bar_data.index, y = stacked_bar_data.total, color = "red")

#Plot 2 - overlay - "bottom" series
bottom_plot = sns.barplot(x = stacked_bar_data.index, y = stacked_bar_data.attended, color = "#0000A3")

topbar = plt.Rectangle((0,0),1,1,fc="red", edgecolor = 'none')
bottombar = plt.Rectangle((0,0),1,1,fc='#0000A3',  edgecolor = 'none')
l = plt.legend([bottombar, topbar], ['var1', 'var2'], loc=1, ncol = 2, prop={'size':18})
l.draw_frame(False)

#Optional code - Make plot look nicer
sns.despine(left=True)
bottom_plot.set_ylabel("Count")
# bottom_plot.set_xlabel("date")

#Set fonts to consistent 16pt size
for item in ([bottom_plot.xaxis.label, bottom_plot.yaxis.label] +
             bottom_plot.get_xticklabels() + bottom_plot.get_yticklabels()):
    item.set_fontsize(16)

# making sure our xticks is formatted correctly
plt.xticks(fontsize=20)
years = mdates.YearLocator()   # every year
months = mdates.MonthLocator()  # every month
years_fmt = mdates.DateFormatter('%Y')

bottom_plot.xaxis.set_major_locator(years)
bottom_plot.xaxis.set_major_formatter(years_fmt)
bottom_plot.xaxis.set_minor_locator(months)
plt.show()
# bottom_plot.axes.xaxis.set_visible(False)

Thing is, my chart doesn't show me the years at the bottom. I believe I have all the pieces necessary to solve this problem, but for some reason I can't figure out what I'm doing wrong.

I think I'm doing something wrong with how I set up the subplots of the sns.barplot . Maybe I should be assigning them to fig and ax or something like that? That's how I saw it done on the matplotlib site . I just can't managed to transfer that logic over to my example.

Any help would be most appreciated. Thanks!

Answer 1

There are few things to consider. First of all, please try to convert your date column ( new_df.date ) to datetime.

new_df.date = pd.to_datetime(new_df.date)

Second of all do not use this part:

bottom_plot.xaxis.set_major_locator(years)
bottom_plot.xaxis.set_major_formatter(years_fmt)
bottom_plot.xaxis.set_minor_locator(months)

Instead use:

x_dates = stacked_bar_data['date'].dt.strftime('%Y').sort_values().unique()
bottom_plot.set_xticklabels(labels=x_dates, rotation=0, ha='center')

This is because seaborn re-locates the bars to integer positions. Even if we set them to be dates - Note, that you used indices explicitly. Below is fully working example. Note - this gives you major ticks only. You'll have to work the minor ticks out. My comments and things I've commented out after double #.

stacked_bar_data.date = pd.to_datetime(stacked_bar_data.date)

stacked_bar_data["total"] = stacked_bar_data.var1 + stacked_bar_data.var2

#Set general plot properties
sns.set_style("whitegrid")
sns.set_context({"figure.figsize": (14, 7)})  ## modified size :)
sns.set_context("poster")

years = mdates.YearLocator()   # every year
months = mdates.MonthLocator()  # every month
years_fmt = mdates.DateFormatter('%Y')

sns.barplot(x = stacked_bar_data.index, y = stacked_bar_data.total, color = "red")
bottom_plot = sns.barplot(x = stacked_bar_data.index, y = stacked_bar_data.attended, color = "#0000A3")

topbar = plt.Rectangle((0,0),1,1,fc="red", edgecolor = 'none')
bottombar = plt.Rectangle((0,0),1,1,fc='#0000A3',  edgecolor = 'none')
l = plt.legend([bottombar, topbar], ['var1', 'var2'], loc=1, ncol = 2, prop={'size':18})
l.draw_frame(False)

#Optional code - Make plot look nicer
sns.despine(left=True)
bottom_plot.set_ylabel("Count")
# bottom_plot.set_xlabel("date")

# making sure our xticks is formatted correctly
## plt.xticks(fontsize=20) # not needed as you change font below in the loop

## Do not use at all
## bottom_plot.xaxis.set_major_locator(years)
## bottom_plot.xaxis.set_major_formatter(years_fmt)
## bottom_plot.xaxis.set_minor_locator(months)

#Set fonts to consistent 16pt size
for item in ([bottom_plot.xaxis.label, bottom_plot.yaxis.label] +
            bottom_plot.get_xticklabels() + bottom_plot.get_yticklabels()):
    item.set_fontsize(16)

## This part is required if you want to stick to seaborn
## This is because the moment you start using seaborn it will "re-position" the bars
## at integer position rather than dates. W/o seaborn there is no such need
x_dates = stacked_bar_data['date'].dt.strftime('%Y').sort_values().unique()
bottom_plot.set_xticklabels(labels=x_dates, rotation=0, ha='center')

plt.show()