I want to export a Pandas DataFrame to LaTeX with . as a thousand seperator and , as a decimal seperator and two decimal digits. E.g. 4.511,34
import numpy as np
import pandas as pd
df = pd.DataFrame(
np.array([[4511.34242, 4842.47565]]),
columns=['col_1', 'col_2']
)
df.to_latex('table.tex', float_format="{:0.2f}".format)
Ho can I achieve this? If I change the . to an , in the code I receive ValueError: Invalid format specifier. Thank you!
As of pandas v1.3.0, you can specify the decimal and thousands separators with the Styler object:
df = df.style.format(decimal=',', thousands='.', precision=2)
>>> df.to_latex()
\begin{tabular}{lrr}
{} & {col_1} & {col_2} \\
0 & 4.511,34 & 4.842,48 \\
\end{tabular}
Apparently, it works with:
import locale
import numpy as np
import pandas as pd
locale.setlocale(locale.LC_ALL, '')
pd.options.display.float_format = '{:n}'.format
df = pd.DataFrame(
np.array([[4511.34242, 4842.47565]]),
columns=['col_1', 'col_2']
)
df.to_latex('table.tex')
But I guess there is a better answer which works only for the exported df!
I would format with _ as the thousands seperator and . as the decimal seperator and then replace those with str.replace.
df.applymap(lambda x: str.format("{:0_.2f}", x).replace('.', ',').replace('_', '.')).to_latex('table.tex')
Gives the following latex:
\begin{tabular}{lll}
\toprule
{} & col\_1 & col\_2 \\
\midrule
0 & 4.511,34 & 4.842,48 \\
\bottomrule
\end{tabular}