Tips for displaying only the decimal component in heatmap annotation floats

Question

Tips for displaying only the decimal component in heatmap annotation floats

I have decimal floats and I'm only concerned with the numbers after the decimal point, as the integer part is irrelevant for my problem.

When displaying these numbers on seaborn plots, I need to use string formatting. Currently, I am using '0.2f' to show two decimal places, but I want to remove the integer part altogether.

For example, instead of showing 0.25, I would like to display .25.

Specifically, I need this implementation to work with formatting values in seaborn.heatmap:

sns.heatmap(table, annot = True, fmt = '.2f')

However, I want to only show the decimals without the leading zero, as mentioned above.

python pandas seaborn string-formatting plot-annotations

Answer 1

Answer №1

According to the information provided by How can we use f-string formatting for Pandas?, it is possible to utilize an f-string within a list-comprehension along with .apply to format all columns in the dataframe. This formatted data can then be passed to annot= using fmt=''.
- Each value undergoes formatting using f'{v:.2f}'[-3:] where .2f is responsible for rounding to two decimal places, and [-3:] extracts the last three characters (e.g., .xx).
- A typical solution involving pandas attempts to avoid the use of .apply, but when dealing with large dataframes for sns.heatmap, there should be no significant impact on performance.

import seaborn as sns
import numpy as np  # for random data

# sample data
np.random.seed(20231118)
df = pd.DataFrame(np.random.random(size=(6, 6)))

# create a new f-string formatted dataframe; resulting in string dtype
annot = df.apply(lambda col: [f'{v:.2f}'[-3:] for v in col], axis=0)

# plot with annotations
ax = sns.heatmap(data=df, fmt='', annot=annot, cbar=False)

https://i.stack.imgur.com/PImh0.png

`df`

          0         1         2         3         4         5
0  0.321406  0.647402  0.173481  0.885630  0.206138  0.584212
1  0.617528  0.782675  0.071267  0.858961  0.689791  0.093260
2  0.161312  0.069866  0.047737  0.804141  0.523107  0.635975
3  0.508007  0.890942  0.435791  0.281811  0.560090  0.384583
4  0.264682  0.501962  0.492275  0.143144  0.629373  0.445461
5  0.883968  0.207125  0.946935  0.222533  0.001788  0.622386

`annot`

     0    1    2    3    4    5
0  .32  .65  .17  .89  .21  .58
1  .62  .78  .07  .86  .69  .09
2  .16  .07  .05  .80  .52  .64
3  .51  .89  .44  .28  .56  .38
4  .26  .50  .49  .14  .63  .45
5  .88  .21  .95  .22  .00  .62

Answer 2

According to the information provided by How can we use f-string formatting for Pandas?, it is possible to utilize an f-string within a list-comprehension along with .apply to format all columns in the dataframe. This formatted data can then be passed to annot= using fmt=''.
- Each value undergoes formatting using f'{v:.2f}'[-3:] where .2f is responsible for rounding to two decimal places, and [-3:] extracts the last three characters (e.g., .xx).
- A typical solution involving pandas attempts to avoid the use of .apply, but when dealing with large dataframes for sns.heatmap, there should be no significant impact on performance.

import seaborn as sns
import numpy as np  # for random data

# sample data
np.random.seed(20231118)
df = pd.DataFrame(np.random.random(size=(6, 6)))

# create a new f-string formatted dataframe; resulting in string dtype
annot = df.apply(lambda col: [f'{v:.2f}'[-3:] for v in col], axis=0)

# plot with annotations
ax = sns.heatmap(data=df, fmt='', annot=annot, cbar=False)

https://i.stack.imgur.com/PImh0.png

`df`

          0         1         2         3         4         5
0  0.321406  0.647402  0.173481  0.885630  0.206138  0.584212
1  0.617528  0.782675  0.071267  0.858961  0.689791  0.093260
2  0.161312  0.069866  0.047737  0.804141  0.523107  0.635975
3  0.508007  0.890942  0.435791  0.281811  0.560090  0.384583
4  0.264682  0.501962  0.492275  0.143144  0.629373  0.445461
5  0.883968  0.207125  0.946935  0.222533  0.001788  0.622386

`annot`

     0    1    2    3    4    5
0  .32  .65  .17  .89  .21  .58
1  .62  .78  .07  .86  .69  .09
2  .16  .07  .05  .80  .52  .64
3  .51  .89  .44  .28  .56  .38
4  .26  .50  .49  .14  .63  .45
5  .88  .21  .95  .22  .00  .62

Answer 3

Answer №2

If you need to extract the two decimal points from a given floating point number, you can use the following code snippet:

float_number = 28.31
formatted_number = "{:.2f}".format(float_number).split('.')[1]

You can then utilize this in a formatter like shown here to customize your plots as needed.

Answer 4

If you need to extract the two decimal points from a given floating point number, you can use the following code snippet:

float_number = 28.31
formatted_number = "{:.2f}".format(float_number).split('.')[1]

You can then utilize this in a formatter like shown here to customize your plots as needed.

Answer 5

Answer №3

If you want to extract only the decimal part of a number, you can use either nb -= int(nb) or decimalPart = nb - int(nb).

Answer 6

If you want to extract only the decimal part of a number, you can use either nb -= int(nb) or decimalPart = nb - int(nb).

Tips for displaying only the decimal component in heatmap annotation floats

Answer №1

`df`

`annot`

Answer №2

Answer №3

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