Constructing pandas DataFrame from values in variables gives \'ValueError: If using all scalar values, you must pass an index\'

Example:

# Importing pandas package

import pandas as pd

# Creating a Dictionary and setting integers as values

dict = {'col_1':10,'col_2':20,'col_3':30}

# Creating a DataFrame

df = pd.DataFrame(dict)

# Print

print(df)

Output:

Solving this error is quite easy, as it says we must pass an index means we have to pass a list of integers and set it as a value inside a dictionary like {'col_1':[10]}.

# Importing pandas package

import pandas as pd

# Creating a Dictionary and setting integers as values

dict = {'col_1':[10],'col_2':[20],'col_3':[30]}

# Creating a DataFrame

df = pd.DataFrame(dict)

# Print

print(df)

Output:

Note: The same logic goes with strings also, i.e., strings too must be passed inside a list and set as a value inside a dictionary otherwise it will raise the same error.

# Importing pandas package

import pandas as pd

# Creating a Dictionary and setting integers as values

dict = {'col_1':'Hello','col_2':'dear','col_3':'World'}

# Creating a DataFrame

df = pd.DataFrame(dict)

# Print

print(df)

Error:

Passing the string inside the list while creating a dictionary would resolve this error.

# Importing pandas package

import pandas as pd

# Creating a Dictionary and setting integers as values

dict = {'col_1':['Hello'],'col_2':['dear'],'col_3':['World']}

# Creating a DataFrame

df = pd.DataFrame(dict)

# Print

print(df)

Output: