Write/ Read columns of list of numbers (integer or float) to/ from CSV in Python [duplicate]

Question

My data consists of 4 columns. They are Name, Age, Seq_1, Seq_2.

For a row (an instance) in my data, its Name and Age are in string and integer, respectively. Seq_1 is an array of numbers. It can be float or integer. Different rows can have Seq_1 with different lengths. Same applies for Seq_2.

I have stored the whole table in DataFame, as df.

> type(df), type(df.Seq_1), type(df.loc[0].Seq_1)
(pandas.core.frame.DataFrame, pandas.core.series.Series, list)

I try to write/ read df from/to csv using

df = pd.read_csv("../data/df.csv", low_memory=False)
df.to_csv("../data/df.csv", index=False)

The problem is: After I write/ read df, the nature of list of numbers of df.loc[0].Seq_1 is lost. Before write/ read, I can access the entry in df.loc[0].Seq_1 by df.loc[0].Seq_1[0]. After write/ read, it seems df.loc[0].Seq_1 is casted into string. df.loc[0].Seq_1[0] returns the first character.

For example, before write/ read, df.loc[0].Seq_1[0] returns -2. after write/ read, df.loc[0].Seq_1[0] returns -.

Thanks in advance.

León · Accepted Answer · 2025-02-05 07:29:49Z

1

This is a duplicate of this question. I use ast.literal_eval given in the second answer.

Pandas DataFrame stored list as string: How to convert back to list

df.Seq_1 = df.Seq_1.apply(literal_eval)

answered Feb 5 at 7:29

León

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1 Comment

Coleman YU Feb 5 at 7:45

Thanks, I can now import the data correctly by pd.read_csv("../data/df.csv", converters={'Seq_1': literal_eval}, low_memory=False). I am interested is there something we can do on the exporting side instead of the importing side, as shown above?

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