CODEWITHSUNDEEP
python-3.xpandasscikit-learnsklearn-pandas
chetan parmar
chetan parmar

Reputation: 73

Merge predicted results into dataframe

In my predicted dataframe I have three columns, I want to merge all those three columns with the original dataset. How can I achieve this?

ds = pd.read_csv("final10.csv")
X = ds.iloc[:, 3:-4].values
y = ds.iloc[:,-1].values
testcase = pd.read_csv("testcase.csv")
testcase=testcase.iloc[:,3:-1].values

from sklearn.linear_model import LogisticRegression
clf = LogisticRegression(solver="newton-cg", multi_class='multinomial')
clf.fit(X, y)
y_pred1 = clf.predict_proba(testcase)
testcase['procurement']=pd.Series(y_pred1)

The error I'm getting is "Exception: Data must be 1-dimensional"

Upvotes: 0

Views: 1221

Answers (1)

Vivek Kumar
Vivek Kumar

Reputation: 36609

You are trying to assign 3 columns in y_pred1 to a single column in dataframe testcase. Thats the source of error. You will have to use three different target columns in the dataframe to assign the three prediction columns.

So for example, if your y has three unique classes (labels) in the data, the predict_proba() output (y_pred1 in this case) will be of shape [n, 3].

You can combine this 2-d array to the existing dataframe in multiple ways:

Simple way: Assign each column separately

testcase['procurement_class0'] = y_pred1[:,0]
testcase['procurement_class1'] = y_pred1[:,1]
testcase['procurement_class2'] = y_pred1[:,2]

Other ways: Look into these questions here:

Upvotes: 1

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