Organizing a csv file of multiple datasets into a list of Pandas dataframes
It is possible to solve this problem procedurally by thinking line-by-line or streamline-by-streamline.
For each streamline that can be matched with IntegrationTime == 0.0, extract the slice from the data frame, and append the slide to an output list (if it has more than 1 data point). A code like the following should address this problem:
import pandas as pd

# read the dataset
df = pd.read_csv(&quot;vel.csv&quot;)

# get row indexes where integrationtime is zero (start of each streamline)
start_index_list = df.loc[df['IntegrationTime']==0.0].index.values
stream_line_list = [] # the output list

for i in range(len(start_index_list)):
    # for each stream line, obtain the slice of the original dataframe that corresponds to it
    start_index = start_index_list[i]
    end_index = None
    if i+1 &lt; len(start_index_list):
        end_index = start_index_list[i+1]-1
    stream_line_df = df.loc[start_index:end_index]
    # only append streamline with more than 1 data point
    if len(stream_line_df) &gt; 1:
        stream_line_list.append(stream_line_df)
    
print(f&quot;number of complete streamlines found: {len(stream_line_list)}&quot;)
```