title: How to plot a scatter plot using a pandas dataframe where the x-axis values are n minus 1 columns and the last column is the dependent variable?
body: <p>I have a dataframe (df), let's say it has 12 columns. I need to plot scatterplots of 11 of those columns (my independent variables) against a single column (my dependent variable). In other words, if my column names are 'x1','x2','x3',...'x11', and 'y12' I want to create a 3 by 4 array of scatterplots; all scatterplots will share the same y-axis values 'y12', and each scatterplot will have a different dependent variable ('x1' for the first one, 'x2' for the second scatterplot, and so forth). </p>
  
  <p>I am working with the pandas and matplotlib.pyplot libraries and I need help troubleshooting the following script:</p>
  
  <pre class="lang-py prettyprint-override"><code>    def plot_df_scatter_columns(x):
      row = [0,1,2]
      column = [0,1,2,3]
      for z in x:
          fig, axes = plt.subplots(3,4, figsize = (12, 8))
  
          for i,j in row, column:
              axes[i, j].scatter(df[x], df['y12'])
              axes[i, j].set_title(df.columns[x]+'vs. y12')
      return plt
      plot_df_scatter_columns(df)
  
  </code></pre>
  
  <p>I expect to see a 3 by 4 array of scatterplots with the same dependent variable ('y12' in the y-axis) and each scatterplot having a unique independent variable (x-axis value). Also, each scatterplot will have a unique title that corresponds to the column that was used as the independent variable (x-axis) from my dataframe. </p>
  
  <p>However, I get a 3 by 4 array of empty plots with no titles.</p>
  
  <p>Error that pops up while working in jupyter notebook:</p>
  
  <p>ValueError: too many values to unpack (expected 2)</p>