I am attempting to create a graph by querying values in a pandas DataFrame.
In this line:
data1 = [np.array(df.query('type == i')['continuous']
for i in ('Type1', 'Type2', 'Type3', 'Type4')]
I get the error:
UndefinedVariableError: name 'i' is not defined
What am I missing?
The i in your query expression
df.query('type == i')
is literally just the string 'i'. Since there are no extra enclosing quotes around it, pandas interprets it as the name of another column in your DataFrame, i.e. it looks for cases where
df['type'] == df['i']
Since there is no i column, you get an UndefinedVariableError.
It looks like you intended to query where the values in the type column are equal to the string variable named i, i.e. where
df['type'] == 'Type1'
df['type'] == 'Type2' # etc.
In this case you need to actually insert the string i into the query expression:
df.query('type == "%s"' % i)
The extra set of quotes are necessary if 'Type1', 'Type2' etc. are values within the type column, but not if they are the names of other columns in the dataframe.
'Type1', 'Type2' etc. were values in the type column or the names of other columns. In the former case you also need to enclose the string value in quotes within the expression: df.query('type == "%s"' % i)i is the name of a string variable, whose value will change from 'Type1' to 'Type2' etc. as you iterate over the tuple of strings. On each loop iteration you want to insert the current value of the variable i into the query string, hence df.query('type == "%s"' % i) for i in ('Type1', 'Type2', ..., )data1 = [np.array(df.query('type == @i')['continuous']
for i in ('Type1', 'Type2', 'Type3', 'Type4')]
use '@' to refer variables
please refer to documentation, which writes:
You can refer to variables in the environment by prefixing them with an ‘@’ character like @a + b.
I know too late but maybe it helps somebody - use double quotes for i
data1 = [np.array(df.query('type == "i"')['continuous']
