PYTHON

pandas create empty dataframe

# Basic syntax:
import pandas as pd
empty_dataframe = pd.DataFrame()

# Create empty dataframe with column names
empty_dataframe = pd.DataFrame(columns=['your', 'column', 'names'])

# Create empty dataframe with row names
empty_dataframe = pd.DataFrame(index=['your', 'row', 'names'])

empty dataframe

newDF = pd.DataFrame() #creates a new dataframe that's empty
newDF = newDF.append(oldDF, ignore_index = True) # ignoring index is optional
# try printing some data from newDF
print newDF.head() #again optional 

create empty pandas dataframe

df = pd.DataFrame(columns=['a', 'b', 'c'])

create an empty dataframe

import pandas as pd
df = pd.DataFrame(columns=['A','B','C','D','E','F','G'])

df empty python

if df.empty:
  print('Your df is empty...')

creating empty data frame pandas

import pandas as pd

col_names =  ['A', 'B', 'C']
my_df  = pd.DataFrame(columns = col_names)
my_df

create a empty dataframe

#This was first Posted By Hilarious Hornet 
newDF = pd.DataFrame() #creates a new dataframe that's empty
newDF = newDF.append(oldDF, ignore_index = True) # ignoring index is optional
# try printing some data from newDF
print(newDF.head()) #again optional 

dataframe pandas empty

>>> df_empty = pd.DataFrame({'A' : []})
>>> df_empty
Empty DataFrame
Columns: [A]
Index: []
>>> df_empty.empty
True

python empty dataframe

# Create Empty DataFrame with column names
df = pd.DataFrame(columns=['species','name','age'])
df.loc[1] = ['dog','Fido','3']  # Populate Row at index 1 (row 1)
df.loc[2] = ['cat','Felix','2'] # Populate Row at index 2 (row 2)
print(df) 

python pandas create an empty dataframe with columns and data types

#Create empty DataFrame with specific column names & types
df = pd.DataFrame({'Courses': pd.Series(dtype='str'),
                   'Fee': pd.Series(dtype='int'),
                   'Duration': pd.Series(dtype='str'),
                   'Discount': pd.Series(dtype='float')})
# Using NumPy
dtypes = np.dtype(
    [
        ("Courses", str),
        ("Fee", int),
        ("Duration", str),
        ("Discount", float),
        ('date',np.datetime64)
    ]
)
df = pd.DataFrame(np.empty(0, dtype=dtypes))