Target data values are not evenly distributed
From scikitlearn LogisticRegression docs:


  class_weight : dict or ‘balanced’, default: None
  
  Weights associated with classes in the form {class_label: weight}. If
  not given, all classes are supposed to have weight one. The “balanced”
  mode uses the values of y to automatically adjust weights inversely
  proportional to class frequencies in the input data as n_samples /
  (n_classes * np.bincount(y)). Note that these weights will be
  multiplied with sample_weight (passed through the fit method) if
  sample_weight is specified. New in version 0.17:
  class_weight=’balanced’


So try to add class_weight='balanced'in your call to LogisticRegression()

Or maybe if this doesn't work, try to use as trainSet an evenly split dataset: where the number of samples of class 1 is equal to class 0.