Pandas integers handling
Python 3.x doesn't have a limit of integer length. You can us as big integers as you like as long as they fit into your machine's memory. But Pandas uses int64 dtype by default which does have limitations. I had run some experiments (in pandas 0.20.3) and here's what I've found: pd default integer type is int64 maximum int64 value is 2**63-1 creating a series with 2**63 results in dtype uint64 creating a series with 2**63 AND with a negative value results in dtype object creating a series with 2**64 results in OverflowError creating a series with negative value and 2**64 afterwards results in dtype object creating a series with 2**64 and negative value afterwards results in OverflowError Here's some code to test (I'll reformat it one day): In[2]: import pandas as pd In[3]: pd.Series([0, 1]) Out[3]: 0 0 1 1 dtype: int64 In[4]: pd.Series([0, 2**63-1]) Out[4]: 0 0 1 9223372036854775807 dtype: int64 In[5]: pd.Series