Replace record in pandas DataFrame with conditional statement

Question

I would like to change the value of a record in a Dataframe subject to a condition. For instance:

d = pandas.read_csv('output.az.txt', names = varname)
d['uld'] = (d.trade - d.plg25)*(d.final - d.price25)

if d['uld'] > 0:
   d['uld'] = 1
else:
   d['uld'] = 0

I do not understand why the above does not work. Thank you for your help.

Answer 1

Use np.whereto set your data based on simple logical criteria:

In [3]:

df = pd.DataFrame({'uld':np.random.randn(10)})
df
Out[3]:
        uld
0  0.939662
1 -0.009132
2 -0.209096
3 -0.502926
4  0.587249
5  0.375806
6 -0.140995
7  0.002854
8 -0.875326
9  0.148876
In [4]:

df['uld'] = np.where(df['uld'] > 0, 1, 0)
df
Out[4]:
   uld
0    1
1    0
2    0
3    0
4    1
5    1
6    0
7    1
8    0
9    1

What is the reason that you did not succeed:

In [7]:

if df['uld'] > 0:
   df['uld'] = 1
else:
   df['uld'] = 0
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-7-ec7d7aaa1c28> in <module>()
----> 1 if df['uld'] > 0:
      2    df['uld'] = 1
      3 else:
      4    df['uld'] = 0

C:\WinPython-64bit-3.4.3.1\python-3.4.3.amd64\lib\site-packages\pandas\core\generic.py in __nonzero__(self)
    696         raise ValueError("The truth value of a {0} is ambiguous. "
    697                          "Use a.empty, a.bool(), a.item(), a.any() or a.all()."
--> 698                          .format(self.__class__.__name__))
    699 
    700     __bool__ = __nonzero__

ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().

, , True False, , , , . any, all .., df , , pandas : http://pandas.pydata.org/pandas-docs/dev/gotchas.html : ValueError: . a.any() a.all()

np.where , , , false , .

UPDATE

, int astype:

In [23]:
df['uld'] = (df['uld'] > 0).astype(int)
df

Out[23]:
   uld
0    1
1    0
2    0
3    0
4    1
5    1
6    0
7    1
8    0
9    1