在阅读数据时没有直接的方法来分割，但是你可以读取整个文件并利用空白行来分割框架：

df = pd.read_csv('your_file.csv', sep=r'\s+', skip_blank_lines=False)

m = df.isna().all(axis=1)

dfs = [g for _,g in df[~m].groupby(m.cumsum())]

print(dfs)

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输出量：

[    #t    x    # DataFrame #1
 0  0.0  0.0
 1  0.0  1.0
 2  0.0  2.0,
     #t    x    # DataFrame #2
 4  0.0  1.0
 5  0.0  2.0
 6  0.0  3.0]

型

# Read file
with open('filename.txt', 'r') as f:
    raw_data = f.read()

# Seperate each experiment
experiments = raw_data.split('\n\n')

# Split lines
experiments = [lines.split('\n') for lines in experiments]

# Create empty list for all.
all_data = []

for experiment in experiments:
    # Create empty list for each experiment.
    data = {'t':[], 'x':[]}
    for line in experiment:

        # if the first character of line is not a number, ignore ( for #t, x )
        if (not line[0].isdigit()): continue
        
        # split and convert data into int
        t, x = map(int,line.split(' '))

        # append it
        data['t'].append(t)
        data['x'].append(x)

    # append it
    all_data.append(data)

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