how to add a column to a pandas df
#using the insert function:
df.insert(location, column_name, list_of_values)
#example
df.insert(0, 'new_column', ['a','b','c'])
#explanation:
#put "new_column" as first column of the dataframe
#and puts 'a','b' and 'c' as values
#using array-like access:
df['new_column_name'] = value
#df stands for dataframespark add column to dataframe
from pyspark.sql.functions import lit
df = sqlContext.createDataFrame(
[(1, "a", 23.0), (3, "B", -23.0)], ("x1", "x2", "x3"))
df_with_x4 = df.withColumn("x4", lit(0))
df_with_x4.show()add column in spark dataframe
from pyspark.sql.functions import lit
df = sqlContext.createDataFrame(
[(1, "a", 23.0), (3, "B", -23.0)], ("x1", "x2", "x3"))
df_with_x4 = df.withColumn("x4", lit(0))
df_with_x4.show()
## +---+---+-----+---+
## | x1| x2| x3| x4|
## +---+---+-----+---+
## | 1| a| 23.0| 0|
## | 3| B|-23.0| 0|
## +---+---+-----+---+how to add new column to dataframe
# Import pandas package
import pandas as pd
# Define a dictionary containing Students data
data = {'Name': ['Jai', 'Princi', 'Gaurav', 'Anuj'],
'Height': [5.1, 6.2, 5.1, 5.2],
'Qualification': ['Msc', 'MA', 'Msc', 'Msc']}
# Convert the dictionary into DataFrame
df = pd.DataFrame(data)
# Declare a list that is to be converted into a column
address = ['Delhi', 'Bangalore', 'Chennai', 'Patna']
# Using 'Address' as the column name
# and equating it to the list
df['Address'] = address
# Observe the result
dfCopyright © 2021 Codeinu
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