Given a dataframe, I know I can select rows by condition using below syntax:
df[df['colname'] == 'Target Value']
But what about a Series? Series does not have a column (axis 1) name, right?
My scenario is I have created a Series by through the nunique() function:
sr = df.nunique()
And I want to list out the index names of those rows with value 1.
Having failed to find a clear answer on the Net, I resorted to below solution:
for (colname, coldata) in sr.iteritems():
if coldata == 1:
print(colname)
Question: what is a better way to get my answer (i.e list out index names of Series (or column names of the original Dataframe) which has just a single value?)
The ultimate objective was to find which columns in a DF has one and only one unique value. Since I did not know how to do that direct from a DF, I first used nunique() and that gave me a Series. Thus i needed to process the Series with a "== 1" (i.e one and only one)
I hope my question isnt silly.
It is unclear what you want. Whether you want to work on the dataframe or on the Series ?
In case you want to work on the dataframe to to list out the index names of those rows with value 1, you can try:
df.index[df[df==1].any(axis=1)].tolist()
Demo
data = {'Col1': [0, 1, 2, 2, 0], 'Col2': [0, 2, 2, 1, 2], 'Col3': [0, 0, 0, 0, 1]}
df = pd.DataFrame(data)
Col1 Col2 Col3
0 0 0 0
1 1 2 0
2 2 2 0
3 2 1 0
4 0 2 1
Then, run the code, it gives:
[1, 3, 4]
If you want to extract the index of a Series with value 1, you can extract it into a list, as follows:
sr.loc[sr == 1].index.tolist()
or use:
sr.index[sr == 1].tolist()