如何移除Pandas DataFrame的行索引与列标签？

Hey there! Let's get your Pandas DataFrame to output just the raw data—no row indices or column labels included. Here are a few simple, effective methods to achieve exactly what you're looking for:

Method 1: Use to_string() with custom parameters #

The to_string() method lets you customize how your DataFrame is printed. By setting index=False and header=False, you'll suppress both the row indices and column labels entirely:

import pandas as pd
l = [[1,2,3],[4,5,6],[7,8,9]]
New_dataframe = pd.DataFrame(l)
# Print without index and headers
print(New_dataframe.to_string(index=False, header=False))

This will output exactly the format you want:

1 2 3
4 5 6
7 8 9

Method 2: Use to_csv() for space-separated output #

If you prefer a CSV-style approach (with spaces as separators), you can use to_csv() and disable indices/headers to get clean, unlabeled data:

print(New_dataframe.to_csv(sep=' ', index=False, header=False))

This produces the same clean output as above. Note: This method adds a trailing newline, but it's usually negligible for most use cases.

Method 3: Manual row iteration (for full control) #

If you want complete control over how each line is formatted, you can iterate over the DataFrame's values directly, convert each row to a string, and print it:

for row in New_dataframe.values:
    print(' '.join(map(str, row)))

This approach is great if you need to tweak formatting further—like changing separators or adding custom text to individual rows.

内容的提问来源于stack exchange，提问作者Shubham Kuse