ここでは、pandasとmatplotlibを使用して、パイプで区切られたファイルをデータフレームにロードし、列に関する基本情報を表示し、各数値列の値の分布を1つの画像にサブプロットするPythonスクリプトの例を示します。

```python
import pandas as pd
import matplotlib.pyplot as plt

file_path = ‘your_file_path_here.txt’
df = pd.read_csv(file_path, sep=‘|’)

print(df.info())

numeric_columns = df.select_dtypes(include=‘number’).columns

num_plots = len(numeric_columns)
num_rows = int(num_plots**(0.5))
num_cols = num_rows if num_rows*num_rows == num_plots else num_rows+1

fig, axs = plt.subplots(num_rows, num_cols, figsize=(15, 15))

for ax, column in zip(axs.flatten(), numeric_columns):
    sns.histplot(df[column], kde=True, ax=ax)
    ax.set_title(column)

for ax_index in range(len(numeric_columns), len(axs.flatten())):
    fig.delaxes(axs.flatten()[ax_index])

output_path = ‘output_file_path_here.png’
plt.savefig(output_path, dpi=300)
plt.show()
```

your_file_path_here.txt`をパイプで区切られたファイルのパスに置き換えてください。また、`output_file_path_here.png`を保存したい画像の出力ファイルのパスに置き換えてください。
Here’s an example Python script using pandas and matplotlib to load a pipe-separated file into a dataframe, print basic information about the columns, and plot the distribution of values for each numeric column as subplots in a single image.

```python
import pandas as pd
import matplotlib.pyplot as plt

file_path = ‘your_file_path_here.txt’
df = pd.read_csv(file_path, sep=‘|’)

print(df.info())

numeric_columns = df.select_dtypes(include=‘number’).columns

num_plots = len(numeric_columns)
num_rows = int(num_plots**(0.5))
num_cols = num_rows if num_rows*num_rows == num_plots else num_rows+1

fig, axs = plt.subplots(num_rows, num_cols, figsize=(15, 15))

for ax, column in zip(axs.flatten(), numeric_columns):
    sns.histplot(df[column], kde=True, ax=ax)
    ax.set_title(column)

for ax_index in range(len(numeric_columns), len(axs.flatten())):
    fig.delaxes(axs.flatten()[ax_index])

output_path = ‘output_file_path_here.png’
plt.savefig(output_path, dpi=300)
plt.show()
```

Replace `your_file_path_here.txt` with the path to your pipe-separated file, and also replace `output_file_path_here.png` with the output file path for the image you want to save.