How to format seaborn/matplotlib axis tick labels from number to thousands or Millions? (125,436 to 125.4K)
IIUC you can format the xticks and set these:
In[60]:
#generate some psuedo data
df = pd.DataFrame({'num':[50000, 75000, 100000, 125000], 'Rent/Sqft':np.random.randn(4), 'Region':list('abcd')})
df
Out[60]:
num Rent/Sqft Region
0 50000 0.109196 a
1 75000 0.566553 b
2 100000 -0.274064 c
3 125000 -0.636492 d
In[61]:
import matplotlib.pyplot as plt
import matplotlib.ticker as ticker
import seaborn as sns
import pandas as pd
sns.set(style="darkgrid")
fig, ax = plt.subplots(figsize=(8, 5))
palette = sns.color_palette("bright", 4)
g = sns.scatterplot(ax=ax, x="num", y="Rent/Sqft", hue="Region", marker='o', data=df, s=100, palette= palette)
g.legend(bbox_to_anchor=(1, 1), ncol=1)
g.set(xlim = (50000,250000))
xlabels = ['{:,.2f}'.format(x) + 'K' for x in g.get_xticks()/1000]
g.set_xticklabels(xlabels)
Out[61]:
The key bit here is this line:
xlabels = ['{:,.2f}'.format(x) + 'K' for x in g.get_xticks()/1000]
g.set_xticklabels(xlabels)
So this divides all the ticks by 1000
and then formats them and sets the xtick labels
UPDATE Thanks to @ScottBoston who has suggested a better method:
ax.xaxis.set_major_formatter(ticker.FuncFormatter(lambda x, pos: '{:,.2f}'.format(x/1000) + 'K'))
see the docs
The canonical way of formatting the tick labels in the standard units is to use an EngFormatter
. There is also an example in the matplotlib docs.
Here it might look as follows.
import numpy as np; np.random.seed(42)
import matplotlib.pyplot as plt
import matplotlib.ticker as ticker
import seaborn as sns
import pandas as pd
df = pd.DataFrame({"xaxs" : np.random.randint(50000,250000, size=20),
"yaxs" : np.random.randint(7,15, size=20),
"col" : np.random.choice(list("ABC"), size=20)})
fig, ax = plt.subplots(figsize=(8, 5))
palette = sns.color_palette("bright", 6)
sns.scatterplot(ax=ax, x="xaxs", y="yaxs", hue="col", data=df,
marker='o', s=100, palette="magma")
ax.legend(bbox_to_anchor=(1, 1), ncol=1)
ax.set(xlim = (50000,250000))
ax.xaxis.set_major_formatter(ticker.EngFormatter())
plt.show()
Using Seaborn without importing matplotlib:
import seaborn as sns
sns.set()
chart = sns.relplot(x="x_val", y="y_val", kind="line", data=my_data)
ticks = chart.axes[0][0].get_xticks()
xlabels = ['$' + '{:,.0f}'.format(x) for x in ticks]
chart.set_xticklabels(xlabels)
chart.fig
Thank you to EdChum's answer above for getting me 90% there.