pd.read_csv添加名为“未命名:0"的列 [英] pd.read_csv add column named "Unnamed: 0

问题描述

我有一个包含3列的数据框.我用 pd.to_csv(filename)保存然后使用

I have a dataframe with 3 columns. I save with pd.to_csv(filename) and then re-open it with

pd.read_csv(filename, index_col=False)

但是我得到一个包含4列的数据框，最左边的列叫做

But I get a dataframe with 4 columns, with the left-most column called

未命名:0

实际上只是行号.没有它，我怎么能读取csv?

that is actually just the row number. How can I read the csv without it?

谢谢！

推荐答案

您应该尝试:

pd.read_csv('file.csv', index_col=0)

index_col:int或sequence或False，默认为None列用作DataFrame的行标签.如果给出了序列，则为MultiIndex用来.如果您的格式错误的文件末尾带有定界符每行，您可能会认为index_col = False强制熊猫不要使用第一列作为索引(行名)

index_col : int or sequence or False, default None Column to use as the row labels of the DataFrame. If a sequence is given, a MultiIndex is used. If you have a malformed file with delimiters at the end of each line, you might consider index_col=False to force pandas to not use the first column as the index (row names)

示例数据集:

我从Google那里获取了数据集，因此，当我只是尝试使用pd.read_csv导入数据时，它默认显示 Unnamed:0 .

I have taken the dataset from google,So while i'm simply trying to import the data with pd.read_csv it shows the Unnamed: 0 as default.

>>> df = pd.read_csv("amis.csv")
>>> df.head()
   Unnamed: 0  speed  period  warning  pair
0           1     26       1        1     1
1           2     26       1        1     1
2           3     26       1        1     1
3           4     26       1        1     1
4           5     27       1        1     1

因此，为了避免 Unnamed:0 ，我们必须使用 index_col = 0 并获得更好的数据框:

So, Just to avoid the the Unnamed: 0 we have to use index_col=0 and will get the nicer dataframe:

>>> df = pd.read_csv("amis.csv", index_col=0)
>>> df.head()
   speed  period  warning  pair
1     26       1        1     1
2     26       1        1     1
3     26       1        1     1
4     26       1        1     1
5     27       1        1     1

注意:因此，为了更清楚地理解我们说的是 index_col = 0 时，它将第一列作为dataFrame中的索引放置，而不显示为未命名:0 .

Note : So, to make it more explicit to understand when we say index_col=0, it placed the first column as the index in the dataFrame rather appearing as Unnamed: 0 .

希望这会有所帮助.

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