sa 11 ip chapter 11 - Pooja Bhatia Classes Hari Nagar

10. Assume that required libraries (panda and numpy) are imported and dataframe df2 has been created as per questions 4 and 5 above. Predict the output produced by following code fragment :

print(df2[df2[“age”] > 12]) print(df2.head(2)) print(df2.tail(3)) # Solution import pandas as pd, numpy as np my_di = {“name” : [“Jiya”, “Tim”, “Rohan”], “age” : np.array([10,15,20]), “weight” : (75,123,239), “height” :[4.5, 5, 6.1], “siblings” : 1, “gender” : “M”} df2 = pd.DataFrame(my_di, index=my_di[“name”]) df2[“IQ”] = [130, 105, 115] df2[“College”] = pd.Series([“IIT”], index=[“Rohan”]) print(df2[df2[“age”] > 12]) # All […]

9. Assume that required libraries (pandas and numpy) are imported and dataframe df2 has been created as per questions 4 and 5 above. Predict the output produced by following code fragment :

sa 11 ip chapter 11 / PythonCSIP CS IP

print(df2.loc[“Jiya”]) print(df2.loc [“Jiya”,”IQ”]) print(df2.loc[“Jiya”:”Tim”, “IQ”:”College”]) print(df2.iloc[0]) print(df2.iloc[0, 5]) print(df2f2.ilocloc[0:2, 5:8]) # Solution import pandas as pd, numpy as np my_di = {“name” : [“Jiya”, “Tim”, “Rohan”], “age” : np.array([10,15,20]), “weight” : (75,123,239), “height” :[4.5, 5, 6.1], “siblings” : 1, “gender” : “M”} df2 = pd.DataFrame(my_di, index=my_di[“name”]) df2[“IQ”] = [130, 105, 115] df2[“College”] = pd.Series([“IIT”], index=[“Rohan”])

9. Assume that required libraries (pandas and numpy) are imported and dataframe df2 has been created as per questions 4 and 5 above. Predict the output produced by following code fragment : Read More »