to_CSV将np.array保存为字符串而不是列表

Question

I want to save a pandas dataframe as a csv file, the problem is that to_csv is converting the np.array into a string.

I want to save the array as an array, I could not find anything in the documentation that was useful.

sudoku_solution = [a for a in assignment if a > 0]


label = np.reshape(np.array(sudoku_solution*n_splits), 
                   (n_splits, len(sudoku_solution)))

df = pd.DataFrame(zip(label))

path = './data/SplitsLabel.csv'
try:
    df.to_csv(path_or_buf = path, 
              mode = 'a',
              header = False)

solution_sudoku = [123, 345, 894, 324, 321, 321] (list of integers)

n_splits = 3 (integer)

The final results should be something like:

0,[123 345 894 324 321 321]

1,[123 345 894 324 321 321]

3,[123 345 894 324 321 321]

But the result now is:

0,"[123 345 894 324 321 321]"

1,"[123 345 894 324 321 321]"

3,"[123 345 894 324 321 321]"

How do I get rid of those quotes?

Answer 1

I suspect that since your output includes commas that it may be entering quotes to avoid a conflict with the formatting. You could try changing your delimiter to a tab so this conflict doesnt happen. You can also change the "quoting" if the delimiter doesn't work for you.

Check out this link for more info: Pandas: use to_csv() with quotation marks and a comma as a seperator

Answer 2

If you have this same problem, perhaps it will save you some headache by checking in here .

None of the solutions posted there could solve my problem, so here is the code to parse the string and convert it to the format I need:

   df = pd.read_csv(filepath_or_buffer = path_x,
                       header = None, 
                       names = ["i", "clauses"]) 

    #it is sad that I have to do that!
    df["clauses"] = df["clauses"].apply(lambda x: x.replace("[", ""))
    df["clauses"] = df["clauses"].apply(lambda x: x.replace("]", ""))
    df["clauses"] = df["clauses"].apply(lambda x: x.replace("\n", ""))
    df["clauses"] = df["clauses"].apply(lambda x: x.replace(",", ""))
    df["clauses"] = df["clauses"].apply(lambda x: x.split(" "))
    df["clauses"] = df["clauses"].apply(lambda x: np.array([int(i) for i in x]))

    cols = [x for x in range(120060)]
    df_x = pd.DataFrame(columns = cols)

    for i in range(len(df)):   
        df_x = df_x.append(pd.Series(data = {k: df["clauses"][i][k] for k in cols}),
                           ignore_index = True)

    df = pd.read_csv(filepath_or_buffer = path_y,
                       header = None, 
                       names = ["i", "label"]) 

    df_x.astype("int")