DataFrame

[Gk]

How can we create empty dataframe in databricks and how many ways we can create dataframe?

[Anonymous]

@Govardhana Reddy​ :

Method 1:

from pyspark.sql import SparkSession
 
spark = SparkSession.builder.appName("MyApp").getOrCreate()
 
# Create an empty DataFrame with a specified schema
empty_df = spark.createDataFrame([], schema=["column1", "column2", "column3"])
empty_df.show()

Method 2: From dictionary

data = [
  {"name": "Alice", "age": 25},
  {"name": "Bob", "age": 30},
  {"name": "Charlie", "age": 35}
]
df = spark.createDataFrame(data)
df.show()

Method 3: From list of tuples

data = [("Alice", 25), ("Bob", 30), ("Charlie", 35)]
df = spark.createDataFrame(data, schema=["name", "age"])
df.show()

Method 4: From Pandas dataframe

import pandas as pd
 
pdf = pd.DataFrame({
  "name": ["Alice", "Bob", "Charlie"],
  "age": [25, 30, 35]
})
df = spark.createDataFrame(pdf)
df.show()

Method 5: from cvs file

df = spark.read.csv("path/to/file.csv", header=True, inferSchema=True)
df.show()

Method 6: From parquet file

df = spark.read.parquet("path/to/file.parquet")
df.show()

[Vartika]

Hi @Govardhana Reddy​ 

Hope everything is going great.

Does @Suteja Kanuri​'s answer help? If yes, would you be happy to mark an answer as best so that other members can find the solution more quickly? If not, please tell us so we can help you. 

Cheers!