SolClover

import pandas as pd

SolClover

data new_ds;
  input Col_A $ Col_B Col_C;
  datalines;
  X 2 3
  Y 5 6 
  Z 12 13
  ;
run;

SolClover

# Initialise list of lists 
my_data = [['X', 2, 3], ['Y', 5, 6], ['Z', 12, 13]] 
  
# Create Pandas DataFrame 
df = pd.DataFrame(my_data, columns = ['Col_A', 'Col_B', 'Col_C']) 
  
# Print DataFrame
df 

SolClover

# Initialise dictionary of lists
my_data = {'Col_A':['X', 'Y', 'Z'], 'Col_B':[2, 5, 12], 'Col_C':[3, 6, 13]} 
  
# Create DataFrame 
df = pd.DataFrame(my_data) 
  
# Print DataFrame 
df

SolClover

proc import datafile="C:\temp\test.csv"
  out=test_dataset
  dbms=csv
  replace;
  getnames=yes;
run;

SolClover

# Import csv into a new Pandas DataFrame
new_df=pd.read_csv('C:/temp/test.csv')

# You can also specify which columns you want to read in with usecols by either 
   # specifying their name or position
# Using column names
new_df=pd.read_csv('C:/temp/test.csv', usecols=['Name','Surname', 'Height', 'Age'])
# Using column positions
new_df=pd.read_csv('C:/temp/test.csv', usecols=[0,1,2,3])

SolClover

data new_ds;
  set old_ds;
run;

SolClover

# Create new DataFrame based on old DataFrame
# Note, in this example you will create a view. 
   # Hence, your future changes to new_df will affect old_df too
new_df=old_df

# To make an actual copy of a DataFrame use this. 
   # In this case, future changes to new_df will not have an impact on old_df
new_df=old_df.copy()

# Print top 5 records of your new DataFrame

SolClover

/* Filter on one condition */
data my_new_ds;
  set my_ds;
where Col_A>=6;
run;

/* Filter on multiple conditions using AND */
data my_ds;
  set my_ds;
where Col_A>=6 and Col_B=5;

SolClover

# Filter on one condition
new_df=df[df['Col_A']>=6]

# Filter on multiple conditions using AND
new_df=df[(df['Col_A']>=6) & (df['Col_B']==5)]

# Filter on multiple conditions using OR
new_df=df[(df['Col_A']>=6) | (df['Col_B']==1)]

# Create a list and use isin to filter