如何使用來自 python pandas 數據幀的適當方程直接生成 latex 表格圖像？

Question

Related to my recent question on printing \pm in latex with pandas How to print a literal backslash to get \pm in a pandas data frame to generate a proper error bars in a latex table in python? 我還想顯示正確顯示方程式的表格，但我在表格中得到了文字\pm （+ 它的形狀很奇怪）。

有沒有辦法直接從 python 將我的帶有方程式的數據框轉換為 png latex 並將其保存為圖像？

腳本

import pandas as pd

# data = {'first_column':  ['first_value', 'second_value', ...],
#         'second_column': ['first_value', 'second_value', ...],
#          ....
#         }

import pandas as pd

from uutils import put_pm_to_pandas_data

 data = {
     'Initialization': ['Random',
                        'Random2',
                        ],

     'Test Accuracy': ['0.200+-0.029',
                       '0.200+-0.0',
                       ],
 }

# - to pandas table
df = pd.DataFrame(data)
print(df)

# https://stackoverflow.com/questions/70009242/how-does-one-generate-latex-table-images-with-proper-equations-from-python-panda

# - to latex
data = put_pm_to_pandas_data(data)
df = pd.DataFrame(data)

print(df.to_latex(index=False, escape=False))

import matplotlib.pyplot as plt
import pandas as pd
from pandas.plotting import table

# ax = plt.subplot(111, frame_on=False) # no visible frame
ax = plt.gca()
ax.xaxis.set_visible(False)  # hide the x axis
ax.yaxis.set_visible(False)  # hide the y axis

# table(ax, df)  # where df is your data frame
table(ax, df)  # where df is your data frame

plt.show()

# plt.savefig('mytable.png')

有關的：

• 如何將 pandas DataFrame 表保存為 png
• 如何打印文字反斜杠以在 pandas 數據幀中獲取 \pm 以在 python 的 latex 表中生成正確的誤差線？

Answer 1

您沒有向我們提供put_pm_to_pandas_data的定義。 但這是使用DataFrame.replace的解決方案

import matplotlib.pyplot as plt
import pandas as pd
from pandas.plotting import table

def put_pm_df(df):
    return df.replace("\+-", r"$\pm$", regex=True)
    
data = {
     'Initialization': ['Random',
                        'Random2',
                        ],
     'Test Accuracy': ['0.200+-0.029',
                       '0.200+-0.0',
                       ],
}

df = pd.DataFrame(data)
print(df)

df = put_pm_df(df)
print(df)

print(df.to_latex(index=False, escape=False))

ax = plt.gca()
ax.xaxis.set_visible(False)  # hide the x axis
ax.yaxis.set_visible(False)  # hide the y axis

table(ax, df) 

plt.show()

Output

# initial df

  Initialization Test Accuracy
0         Random  0.200+-0.029
1        Random2    0.200+-0.0

# result of put_pm_df(df)

  Initialization    Test Accuracy
0         Random  0.200$\pm$0.029
1        Random2    0.200$\pm$0.0

# df.to_latex(index=False, escape=False)

\begin{tabular}{ll}
\toprule
Initialization &    Test Accuracy \\
\midrule
        Random &  0.200$\pm$0.029 \\
       Random2 &    0.200$\pm$0.0 \\
\bottomrule
\end{tabular}