title: Error: "ValueError: could not convert string to float: 'Private Sector/Self Employed' "
body: <p>Output- &quot;ValueError: could not convert string to float: 'Private Sector/Self Employed' &quot;.</p>
  <p>I need help with this error as I get this error consistently</p>
  <pre><code>import numpy as np # linear algebra
  import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)
  import os
      for dirname, _, filenames in os.walk('/kaggle/input'):
         for filename in filenames:
            print(os.path.join(dirname, filename))
      pd.options.mode.chained_assignment = None # disabled chaining errors as some columns overwritten below
      import sys
      print(sys.version)
      import matplotlib.pyplot as plt
      %matplotlib inline
      from sklearn.preprocessing import LabelEncoder
      from scipy.stats import levene
      import seaborn as sns
      from scipy.stats import shapiro
      from sklearn.model_selection import train_test_split, cross_val_score
      from sklearn.neighbors import KNeighborsClassifier
      from sklearn.tree import DecisionTreeClassifier
      from sklearn.ensemble import RandomForestClassifier
      from sklearn.naive_bayes import GaussianNB
      from sklearn.linear_model import LogisticRegression
      from sklearn.svm import SVC
      from sklearn.metrics import accuracy_score
      from sklearn.preprocessing import StandardScaler
      from sklearn.decomposition import PCA
      from sklearn.decomposition import KernelPCA
      
      
      dataset_df = pd.read_csv(&quot;TravelInsurancePrediction.csv&quot;)
      dataset = dataset_df.loc[:, ~dataset_df.columns.str.contains('^Unnamed')]
      
      X = dataset.iloc[:,:-1].values
      y = dataset.iloc[:, -1].values
      X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.25, random_state = 188)
      cKNN = KNeighborsClassifier(n_neighbors = 10, metric = 'minkowski', p = 2).fit(X_train, y_train)
  </code></pre>