How to format axis tick labels from number to thousands or Millions (125,436 to 125.4K)

Question

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", 6)
g = sns.scatterplot(ax=ax, x="Area", 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))

How can I can change the axis format from a number to custom format? For example, 125000 to 125.00K

Answer 1

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

Answer 2

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.

Also see Tick locating and formatting

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()

Answer 3

Here's how I'm solving this: (similar to ScottBoston)

from matplotlib.ticker import FuncFormatter

f = lambda x, pos: f'{x/10**3:,.0f}K'
ax.xaxis.set_major_formatter(FuncFormatter(f))

Answer 4

We could used the APIs: ax.get_xticklabels() , get_text() and ax.set_xticklabels do it.

e.g,

xlabels = ['{:.2f}k'.format(float(x.get_text().replace('−', '-')))/1000 for x in g.get_xticklabels()]
g.set_xticklabels(xlabels)

Answer 5

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.