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

# Load the pipe-separated file into a pandas DataFrame
file_path = 'your_file_path_here.txt'
df = pd.read_csv(file_path, sep='|')

# Print basic information about the various columns
print(df.info())

# Identify numeric columns
numeric_columns = df.select_dtypes(include=['number']).columns

# Create subplots for each numeric column
fig, axes = plt.subplots(nrows=len(numeric_columns), ncols=1, figsize=(10, 5 * len(numeric_columns)))

# Plot the distribution of values for each numeric column
for idx, column in enumerate(numeric_columns):
    df[column].plot(kind='hist', ax=axes[idx], title=column)

# Adjust the layout and show the plot
plt.tight_layout()
plt.show()
```

'your_file_path_here.txt'`をパイプで区切ったファイルへのパスに置き換えてください。このスクリプトは、ファイルをpandasのDataFrameにロードし、列に関する基本情報を表示し、各数値列のヒストグラムを1つの画像にサブプロットして作成します。
```python
import pandas as pd
import matplotlib.pyplot as plt

# Load the pipe-separated file into a pandas DataFrame
file_path = 'your_file_path_here.txt'
df = pd.read_csv(file_path, sep='|')

# Print basic information about the various columns
print(df.info())

# Identify numeric columns
numeric_columns = df.select_dtypes(include=['number']).columns

# Create subplots for each numeric column
fig, axes = plt.subplots(nrows=len(numeric_columns), ncols=1, figsize=(10, 5 * len(numeric_columns)))

# Plot the distribution of values for each numeric column
for idx, column in enumerate(numeric_columns):
    df[column].plot(kind='hist', ax=axes[idx], title=column)

# Adjust the layout and show the plot
plt.tight_layout()
plt.show()
```

Replace `'your_file_path_here.txt'` with the path to your pipe-separated file. This script will load the file into a pandas DataFrame, print basic information about the columns, and create a histogram for each numeric column in a single image with subplots.