使用熊猫to_csv函数

Question

I have been experimenting with pandas, and while I have figured out how to use it to read data, I have stumbled upon some trouble in writing my output, and need your help!

This is my simplified code:

import pandas as pd

df = pd.DataFrame("prices", "product1", "product2", "product3")
prices = df.prices
product1 = df.product1
product2 = df.product2
product3 = df.product3

prices = ["Price Option 1", "Price Option 2", "Price Option 3"]
product1 = [1,2,3]
product2 = [4,5,6]
product3 = [7,8,9]

df.to_csv("output.csv") 

The expected output was supposed to be something like:

prices    product1    product2    product3
price1       1           2           3
price2       4           5           6
price3       7           8           9

But instead I get this error:

Traceback (most recent call last):
  File "output.py", line 3, in <module>
    df = pd.DataFrame("prices", "product1", "product2", "product3")
  File "C:\Python27\lib\site-packages\pandas-0.14.1-py2.7-win32.egg\pandas\core\frame.py", line 194,
 in __init__
    dtype = self._validate_dtype(dtype)
  File "C:\Python27\lib\site-packages\pandas-0.14.1-py2.7-win32.egg\pandas\core\generic.py", line 10
8, in _validate_dtype
    dtype = np.dtype(dtype)
TypeError: data type "product3" not understood

And I'm not quite sure why... Help is much appreciated!

Answer 1

You are constructing your df incorrectly, the following would work:

In [3]:

df = pd.DataFrame(columns=["prices", "product1", "product2", "product3"])
df.prices = ["Price Option 1", "Price Option 2", "Price Option 3"]
df.product1 = [1,2,3]
df.product2 = [4,5,6]
df.product3 = [7,8,9]
df
Out[3]:
           prices  product1  product2  product3
0  Price Option 1         1         4         7
1  Price Option 2         2         5         8
2  Price Option 3         3         6         9

As would putting your data into a dict:

In [4]:

data = {'prices':["Price Option 1", "Price Option 2", "Price Option 3"], 'product1':[1,2,3], 'product2':[4,5,6], 'product3':[7,8,9]}
pd.DataFrame(data)
Out[4]:
           prices  product1  product2  product3
0  Price Option 1         1         4         7
1  Price Option 2         2         5         8
2  Price Option 3         3         6         9

You can then write to csv as normal