title: Dictionary to Dataframe Error: "If using all scalar values, you must pass an index"
body: <p>Currently, I am using a for loop to read csv files from a folder.
  After reading the csv file, I am storing the data into one row of a dictionary.
  When I print the data types using "print(list_of_dfs.dtypes)" I receive:</p>
  
  <p>dtype: object
  DATETIME : object
  VALUE : float64
  ID : int64
  ID Name: object.</p>
  
  <p>Note that this is a nested dictionary with thousands of values stored in each of these data fields. I have 26 rows of the structure listed above. I am trying to append the dictionary rows into a dataframe where I will have only 1 row consisting of the datafields:</p>
  
  <p>Index DATETIME VALUE ID ID Name.</p>
  
  <p>Note: I am learning python as I go.
  I tried using an array to store the data and then convert the array to a dataframe but I could not append the rows of the dataframe.</p>
  
  <p>Using the dictionary method I attempted "df = pd.Dataframe(list_of_dfs)"
  This throws an error.</p>
  
  <pre><code>list_of_dfs = {} 
  
  for I in range(0,len(regionLoadArray)
  list_of_dfs[I] = pd.read_csv(regionLoadArray[I]) 
  
  #regionLoadArray contains my- file names from list directory.
  
  dataframe = pd.DataFrame(list_of_dfs)
  #this method was suggested at thispoint.com for nested dictionaries.
  #This is where my error occurs^
  </code></pre>
  
  <blockquote>
    <p>ValueError: If using all scalar values, you must pass an index</p>
  </blockquote>
  
  <p>I appreciate any assistance with this issue as I am new to python.
  My current goals is to simply produce a dataframe with my Headers that I can then send to a csv.</p>