I am trying to read in data from a text file using numpy.loadtxt with the converters argument. I have a mixture of columns of ints and strings. The code is:

```
a, b, c, d, e = np.loadtxt(infile, delimiter = ',', usecols=(0, 2, 5, 8, 9), skiprows = 1,
                           unpack = True, converters = dict(zip((0, 2, 5, 8, 9), (int, float, float, int, int))))

```

The data are read in correctly and unpacked correctly, but all the variables (a, b, c, d, and e) end up as floats. Am I making a mistake in the converters syntax?

**Edit trying answer**

I tried using dtype = (int,float,float,int,int) as suggested by @joris as:

```
a,b,c,d,e = np.loadtxt(infile,delimiter = ',', usecols=(0,2,5,8,9), skiprows = 1, unpack = True, dtype = (int,float,float,int,int))

```

But I get the following error:

```
     41                                            skiprows = 1,
     42                                            unpack = True,
---> 43                                            dtype = (int,float,float,int,int))
     44
     45

/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/numpy/lib/npyio.pyc in loadtxt(fname, dtype, comments, delimiter, converters, skiprows, usecols, unpack)
    665     try:
    666         # Make sure we're dealing with a proper dtype

--> 667         dtype = np.dtype(dtype)
    668         defconv = _getconv(dtype)
    669

TypeError: data type not understood
WARNING: Failure executing file: <forward_NDMMF.py>

```

I am using NumPy v. 1.5.1.