You can use pandas (the becoming default library for working with dataframes (heterogeneous data) in scientific python) for this. It's `read_csv`

can handle this. From the docs:

quotechar : string

`The character to used to denote the start and end of a quoted item. Quoted items can include the delimiter and it will be ignored.`

The default value is `"`

. An example:

```
In [1]: import pandas as pd
In [2]: from StringIO import StringIO
In [3]: s="""year, city, value
...: 2012, "Louisville KY", 3.5
...: 2011, "Lexington, KY", 4.0"""
In [4]: pd.read_csv(StringIO(s), quotechar='"', skipinitialspace=True)
Out[4]:
year city value
0 2012 Louisville KY 3.5
1 2011 Lexington, KY 4.0
```

The trick here is that you also have to use `skipinitialspace=True`

to deal with the spaces after the comma-delimiter.

Apart from a powerful csv reader, I can also strongly advice to use pandas with the heterogeneous data you have (the example output in numpy you give are all strings, although you could use structured arrays).

Answer:1

The problem with the additional comma, `np.genfromtxt`

does not deal with that.

One simple solution is to read the file with `csv.reader()`

from python's csv module into a list and then dump it into a numpy array if you like.

If you really want to use `np.genfromtxt`

, note that it can take iterators instead of files, e.g. `np.genfromtxt(my_iterator, ...)`

. So, you can wrap a `csv.reader`

in an iterator and give it to `np.genfromtxt`

.

That would go something like this:

```
import csv
import numpy as np
np.genfromtxt(("\t".join(i) for i in csv.reader(open('myfile.csv'))), delimiter="\t")
```

This essentially replaces on-the-fly only the appropriate commas with tabs.

Answer:2

If you are using a numpy you probably want to work with numpy.ndarray. This will give you a numpy.ndarray:

```
import pandas
data = pandas.read_csv('file.csv').as_matrix()
```

Pandas will handle the "Lexington, KY" case correctly

Answer:3

- python using numpy
- python use numpy array
- python use numpy library
- python with numpy
- python with numpy online
- python with numpy download
- python with numpy and pandas
- python with numpy and scipy

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