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Data Engineering
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DataFrame

Gk
New Contributor III

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

2 REPLIES 2

Anonymous
Not applicable

@Govardhana Reddyโ€‹ :

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
Moderator
Moderator

Hi @Govardhana Reddyโ€‹ 

Hope everything is going great.

Does @Suteja Kanuriโ€‹'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!

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