How to Combine Multiple Rows into a Single Row with Pandas

How to combine multiple rows into a single row with pandas

You can use groupby and apply function join :

print df.groupby('value')['tempx'].apply(' '.join).reset_index()
   value                                              tempx
0    1.5  picture1 picture555 picture255 picture365 pict...

Pandas: How to merge all rows into a single row?

Try this:

df = pd.DataFrame({'text': [', '.join(df['text'].str.strip('"').tolist())]})

Output:

>>> df
                 text
0  abc, def, ghi, jkl

How to combine multiple rows into a single row with many columns in pandas using an id (clustering multiple records with same id into one record)

The below code worked for me:

all_task_usage_10_19.groupby('machine_ID')[['start_time_of_the_measurement_period','end_time_of_the_measurement_period','job_ID', 'task_index','mean_CPU_usage_rate', 'canonical_memory_usage',
    'assigned_memory_usage', 'unmapped_page_cache_memory_usage',           'total_page_cache_memory_usage', 'maximum_memory_usage',
    'mean_disk_I/O_time', 'mean_local_disk_space_used','maximum_CPU_usage',
    'maximum_disk_IO_time', 'cycles_per_instruction_(CPI)',
    'memory_accesses_per_instruction_(MAI)', 'sample_portion',
    'aggregation_type', 'sampled_CPU_usage']].agg(list).reset_index()

How do you join multiple rows into one row in pandas?

Create mask for match words by Series.str.contains, invert by ~ and crate groups by Series.cumsum, filter only matched rows and pass to GroupBy.agg with join function:

m = df['list_one'].str.contains('\w+')
df = df[m].groupby((~m).cumsum(), as_index=False).agg(', '.join)
print (df)
                   list_one
0     apple, banana, cherry
1  grape, orange, pineapple

Python & Pandas: combining multiple rows into single cell

You would just need to store the text from each page in a list and combine it all at the end. For example:

import pdfplumber
import csv

with pdfplumber.open('target.pdf') as pdf, \
     open("pdf_text_pgs.csv", "w", newline="", encoding="utf-8") as f_output:

    csv_output = csv.writer(f_output)
    csv_output.writerow(['text'])

    text = []
    
    for page in pdf.pages:
        extracted_text = page.extract_text()
        
        if extracted_text:  # skip empty pages or pages with images
            text.append(extracted_text)
        
    csv_output.writerow([' '.join(text)])

Combine multiple rows of lists into one big list using pandas

use df.explode()

lst = df['fruits'].explode().to_list()

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