Initializing Pandas Dataframe

Dataframe can be initialized in multiple ways. Let's see some of the approaches below

#createing dataframe with
#list of countries, GDP and per capita
countries_df = pd.DataFrame([["Germany",4.150,50206],

                             ["India", 2.454, 7153], 

                             ["USA",18.558,57467]])
print(countries_df)




Result

         0       1      2
0  Germany   4.150  50206
1    India   2.454   7153
2      USA  18.558  57467

#Let's give logical name to columns
countries_df = pd.DataFrame([["Germany",4.150,50206],

                             ["India", 2.454, 7153], 

                             ["USA",18.558,57467]],
                            columns=("Country","GDP","Per Capita")
                            )
print(countries_df)



Result
   Country     GDP  Per Capita
0  Germany   4.150       50206
1    India   2.454        7153
2      USA  18.558       57467


#Let's make country name as index
#Let's give logical name to columns
countries_df = pd.DataFrame([["Germany",4.150,50206],

                             ["India", 2.454, 7153], 

                             ["USA",18.558,57467]],
                            columns=("Country","GDP","Per Capita"),
                            index=("Germany","India","USA")
                            )
print(countries_df)



Result
         Country     GDP  Per Capita
Germany  Germany   4.150       50206
India      India   2.454        7153
USA          USA  18.558       57467


#Dataframe can be created with map also
countries_df = pd.DataFrame([{"Country":"Germany","GDP":4.150,"Per Capita":50206},
                            {"Country":"India","GDP": 2.454, "Per Capita":7153},
                            {"Country":"USA","GDP":18.558,"Per Capita":57467}
                           ])
print(countries_df)


Result

   Country     GDP  Per Capita
0  Germany   4.150       50206
1    India   2.454        7153
2      USA  18.558       57467

#Dataframe with NaN values
nan_df = pd.DataFrame(np.nan, index=[0,1,2], columns=("Country","GDP","Per Capita"))
print(nan_df)



Result

   Country  GDP  Per Capita
0      NaN  NaN         NaN
1      NaN  NaN         NaN
2      NaN  NaN         NaN

#Putting all values to 0
zero_df = pd.DataFrame(0,index=[0,1,2], columns=("Country","GDP","Per Capita"))
print(zero_df)



Result

   Country  GDP  Per Capita
0        0    0           0
1        0    0           0
2        0    0           0

GitHub code