pivot_list_melt.py

data_columns = ['killID', 'solarSystemID', 'killTime', 'moonID']
pivot_column = 'items'
index_column = 'killID'

## Make source DataFrame ##
raw_df = pd.DataFrame(raw_data)

## Rotate list-column into its own frame ##
pivot_df = pd.DataFrame(list(raw_df[pivot_column]))
pivot_df = pd.concat(raw_df[index_column, pivot_df], axis=1) #add index to frame

## Melt down data column into a single column ##
pivot_df = pd.melt(pivot_df, id_vars=[index_column])  #compress arbitrary-len data into one col
pivot_df.dropna(axis=0, how='any', inplace=True)  #remove blank rows

## Apply dict-pivot to data ##
value_df = pd.DataFrame(list(pivot_df['value']))  
value_df = pd.concat([pivot_df[index_column], value_df], axis=1) #add index to frame

## Merge source/pivot together ##
result_df = raw_df.join(value_df, index_column, lsuffix='_')

## Tidy DF ##
data_columns.extend(list(value_df.columns.values))
drop_columns = list(set(result_df.columns.values) - set(data_columns))
result_df = result_df.drop(drop_columns, 1)

result_df.csv