#!/usr/bin/env python
# coding: utf-8

# # Creating a [`DataFrame`](https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.html#pandas.DataFrame)

# There are actually quite a few ways to create a [`DataFrame`](https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.html) from existing objects.
# 
# Let's explore!

# In[1]:


# Setup
import pandas as pd


# ## From a 2-dimensional object

# If your data is already in rows and columns you can just pass it along to the constructor.  Labels and Column headings will be automatically generated as a range.

# In[2]:


test_users_list = [
    ['Craig', 'Dennis', 42.42],
    ['Treasure', 'Porth', 25.00]
]

pd.DataFrame(test_users_list)


# Notice how both the labels and column headings are autogenerated. You can specify the `index` and `columns`.

# In[3]:


pd.DataFrame(test_users_list, index=['craigsdennis', 'treasure'],
            columns=['first_name', 'last_name', 'balance'])


# ## From a dictionary

# Much like a `Series`, if you do not specify the index it will be autogenerated in range format.

# In[4]:


# Default expected Dictionary layout is column name, to ordered values
test_user_data = {
    'first_name': ['Craig', 'Treasure'],
    'last_name': ['Dennis', 'Porth'],
    'balance': [42.42, 25.00]
}

pd.DataFrame(test_user_data)


# And remember that can specify the index by supplying the `index` keyword argument.

# In[5]:


pd.DataFrame(test_user_data, index=['craigsdennis', 'treasure'])


# ### [`DataFrame.from_dict`](https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.from_dict.html#pandas.DataFrame.from_dict) adds more options

# #### The `orient` keyword
# The orient keyword allows you to specify whether the keys of your dictionary are part of the labels (`index`) or the column titles (`columns`). Note how the nested dictionaries have been used to define the columns. You could also pass a list to the `columns` 

# In[6]:


by_username = {
    'craigsdennis': {
        'first_name': 'Craig',
        'last_name': 'Dennis',
        'balance': 42.42
    },
    'treasure': {
        'first_name': 'Treasure',
        'last_name': 'Porth',
        'balance': 25.00
    }
}

pd.DataFrame.from_dict(by_username, orient='index')