Q:

Python - Access column based on another column value

I have the following dataframe in python
+-------+--------+
| Value | Number |
+-------+--------+
| true  |    123 |
| false |    234 |
| true  |    345 |
| true  |    456 |
| false |    567 |
| false |    678 |
| false |    789 |
+-------+--------+

How do I conduct an operation which returns a list of all the 'Number' which has Value == TRUE
The output list expected from the above table is
['123', '345', '456']

Thanks in advance!

A:

df.loc[df['Value'],'Number'] should work assuming the dtype for 'Value' are real booleans:
In [68]:
df.loc[df['Value'],'Number']

Out[68]:
0    123
2    345
3    456
Name: Number, dtype: int64

The above uses boolean indexing, here the boolean values are a mask against the df.
If you want a list:
In [69]:
df.loc[df['Value'],'Number'].tolist()

Out[69]:
[123, 345, 456]

