Data Analytics

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1. What is the output of this code?

import pandas as pd
idx = pd.Index(['a', 'b', 'c'])
print(idx.is_unique)

A. False B. True C. Raises AttributeError D. None Correct answer: B. 2. What does this code return?

import pandas as pd
df = pd.DataFrame({'a': [1, 2, 3]})
print(df.set_index('a').index.name)

A. None B. 'index' C. 'a' D. Raises KeyError Correct answer: C. 3. What is the result?

import pandas as pd
s = pd.Series([1, 2, 3])
print(s.add(1).tolist())

A. [1, 2, 3] B. [2, 3, 4] C. [1, 3, 5] D. Error Correct answer: B. 4. What does this code output?

import pandas as pd
df = pd.DataFrame({'a': [1, 2, 3]})
print(df.nlargest(2, 'a')['a'].tolist())

A. [1, 2] B. [2, 3] C. [3, 2] D. [3, 1] Correct answer: C. 5. What is printed?

import pandas as pd
df = pd.DataFrame({'a': [1, 2, 3]})
print(df.nsmallest(1, 'a').iloc[0, 0])

A. 1 B. 2 C. 3 D. Error Correct answer: A. 6. What does this code return?

import pandas as pd
s = pd.Series([1, 2, 3])
print(s.diff().isna().sum())

A. 0 B. 1 C. 2 D. 3 Correct answer: B. 7. What is the output?

import pandas as pd
df = pd.DataFrame({'a': [1, 2, 3]})
print(df.cumsum()['a'].iloc[-1])

A. 3 B. 5 C. 6 D. Error Correct answer: C. 8. What does this code produce?

import pandas as pd
df = pd.DataFrame({'a': [1, 2], 'b': [3, 4]})
print(df.pipe(lambda x: x.shape))

A. (1, 4) B. (2, 2) C. (4, 1) D. Error Correct answer: B. 9. What is returned?

import pandas as pd
s = pd.Series([10, 20, 30])
print(s.take([2, 0]).tolist())

A. [10, 20] B. [30, 10] C. [20, 30] D. Error Correct answer: B. 10. What does this output?

import pandas as pd
df = pd.DataFrame({'a': [1, 2, 3]})
print(df.any().iloc[0])

A. False B. True C. None D. Error Correct answer: B. 11. What is the result?

import pandas as pd
df = pd.DataFrame({'a': [0, 0, 1]})
print(df.all().iloc[0])

A. True B. False C. None D. Error Correct answer: B. 12. What does this code return?

import pandas as pd
s = pd.Series(['a', 'b', 'c'])
print(s.repeat(2).shape)

A. (3,) B. (6,) C. (2, 3) D. Error Correct answer: B. 13. What is printed?

import pandas as pd
df = pd.DataFrame({'a': [1, 2, 3]})
print(df.melt().shape)

A. (1, 3) B. (3, 2) C. (3, 1) D. (1, 2) Correct answer: B. 14. What does this code output?

import pandas as pd
df = pd.DataFrame({'a': [1, 2, 3]})
print(df.stack().shape)

A. (3,) B. (3, 1) C. (1, 3) D. Error Correct answer: A. 15. What is the result?

import pandas as pd
df = pd.DataFrame({'a': [1, 2, 3]})
print(df.unstack().isna().sum().sum())

A. 0 B. 1 C. 2 D. Error Correct answer: A. 16. What does this code return?

import pandas as pd
s = pd.Series([1, 2, 3])
print(s.to_numpy().ndim)

A. 0 B. 1 C. 2 D. Error Correct answer: B. 17. What is printed?

import pandas as pd
df = pd.DataFrame({'a': [1, 2, 3]})
print(df.axes[0].equals(df.index))

A. True B. False C. None D. Error Correct answer: A. 18. What does this code output?

import pandas as pd
df = pd.DataFrame({'a': [1, 2, 3]})
print(df.copy(deep=False) is df)

A. True B. False C. None D. Error Correct answer: B. 19. What is the result?

import pandas as pd
s = pd.Series([1, 2, 3])
print(s.equals(pd.Series([1, 2, 3])))

A. True B. False C. None D. Error Correct answer: A. 20. What does this code output?

import pandas as pd
df = pd.DataFrame({'a': [1, 2, 3]})
print(df.info() is None)

A. True B. False C. None D. Error Correct answer: A.

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I have sent you some real and important questions based on my reading of the book "Pandas Cookbook 2025".

1. What is the output of this code?

import pandas as pd
s = pd.Series([1, 2, 3], index=['a', 'b', 'c'])
print(s.reindex(['c', 'a', 'd']))

A. Series with values [3, 1, NaN] B. Series with values [3, 1] C. KeyError D. Series with values [1, 3, NaN] Correct answer: A. 2. What does this code produce?

import pandas as pd
df = pd.DataFrame({'a': [1, 2], 'b': [3, 4]})
print(df.assign(c=lambda x: x['a'] + x['b'])['c'].iloc[1])

A. 3 B. 4 C. 5 D. 6 Correct answer: C. 3. What is the result?

import pandas as pd
df = pd.DataFrame({'a': [1, 2, 3]})
df.loc[df['a'] > 1, 'a'] = 0
print(df['a'].tolist())

A. [1, 2, 3] B. [1, 0, 0] C. [0, 0, 0] D. [1, 2, 0] Correct answer: B. 4. What does this output?

import pandas as pd
s = pd.Series([10, 20, 30], index=[2, 0, 1])
print(s.sort_index().iloc[0])

A. 10 B. 20 C. 30 D. IndexError Correct answer: B. 5. What is returned?

import pandas as pd
df = pd.DataFrame({'a': [1, 1, 2]})
print(df['a'].value_counts().loc[1])

A. 1 B. 2 C. 3 D. KeyError Correct answer: B. 6. What does this code output?

import pandas as pd
s = pd.Series([1, 2, 3])
print(s.map({1: 'a', 2: 'b'}).isna().sum())

A. 0 B. 1 C. 2 D. 3 Correct answer: B. 7. What is the result?

import pandas as pd
df = pd.DataFrame({'a': [1, None, 3]})
print(df['a'].astype('Int64').isna().sum())

A. 0 B. 1 C. 2 D. Raises error Correct answer: B. 8. What does this produce?

import pandas as pd
df = pd.DataFrame({'a': [1, 2], 'b': [3, 4]})
print(df.filter(regex='a').shape)

A. (1, 2) B. (2, 1) C. (2, 2) D. (1, 1) Correct answer: B. 9. What is printed?

import pandas as pd
s = pd.Series(['1', '2', '3'])
print(s.str.cat(sep='-'))

A. 1-2-3 B. ['1-2-3'] C. Series D. Error Correct answer: A. 10. What does this code return?

import pandas as pd
df = pd.DataFrame({'a': [1, 2, 3]})
print(df.sample(n=1).shape)

A. (3, 1) B. (1, 3) C. (1, 1) D. Depends on random seed Correct answer: C. 11. What is the result?

import pandas as pd
s = pd.Series([1, 2, 3, 4])
print(s.rolling(2).sum().iloc[-1])

A. 4 B. 5 C. 6 D. NaN Correct answer: B. 12. What does this output?

import pandas as pd
df = pd.DataFrame({'a': [1, 2, 3]})
print(df.eval('b = a * 2').shape)

A. (3, 1) B. (3, 2) C. (1, 3) D. Error Correct answer: B. 13. What is returned?

import pandas as pd
df = pd.DataFrame({'a': [1, 2, 3]})
print(df.query('a % 2 == 0')['a'].iloc[0])

A. 1 B. 2 C. 3 D. KeyError Correct answer: B. 14. What does this code output?

import pandas as pd
s = pd.Series([1, 2, 3])
print(s.to_frame().shape)

A. (1, 3) B. (3, 1) C. (3, 3) D. (1, 1) Correct answer: B. 15. What is the result?

import pandas as pd
df = pd.DataFrame({'a': [1, 2]})
print(df.T.shape)

A. (2, 1) B. (1, 2) C. (2, 2) D. (1, 1) Correct answer: B. 16. What does this print?

import pandas as pd
df = pd.DataFrame({'a': [1, 2, 3]})
print(df.shift(1)['a'].isna().sum())

A. 0 B. 1 C. 2 D. 3 Correct answer: B. 17. What is the output?

import pandas as pd
df = pd.DataFrame({'a': [1, 2, 3]})
print(df.duplicated().any())

A. True B. False C. None D. Error Correct answer: B. 18. What does this code return?

import pandas as pd
s = pd.Series([3, 1, 2])
print(s.rank().tolist())

A. [3, 1, 2] B. [1, 2, 3] C. [3.0, 1.0, 2.0] D. [3.0, 1.0, 2.0] sorted Correct answer: C. 19. What is printed?

import pandas as pd
df = pd.DataFrame({'a': [1, 2, 3]})
print(df.memory_usage(deep=True).iloc[1] > 0)

A. True B. False C. None D. Error Correct answer: A. 20. What does this produce?

import pandas as pd
df = pd.DataFrame({'a': [1, 2, 3]})
print(df.select_dtypes(include='int').shape)

A. (3, 0) B. (0, 1) C. (3, 1) D. (1, 3) Correct answer: C.

1. What is the result of the following code?

import pandas as pd
s = pd.Series([10, 20, 30], index=[1, 2, 3])
print(s[1])

A. 10 B. 20 C. 30 D. KeyError Correct answer: A. 2. What will this code output?

import pandas as pd
s = pd.Series([10, 20, 30])
print(s.iloc[1])

A. 10 B. 20 C. 30 D. IndexError Correct answer: B. 3. What does this print?

import pandas as pd
df = pd.DataFrame({"a": [1, 2], "b": [3, 4]})
print(df.shape)

A. (4,) B. (2, 2) C. (1, 4) D. (2,) Correct answer: B. 4. What is returned by this expression?

df["a"]

A. DataFrame B. Series C. list D. ndarray Correct answer: B. 5. What does this code output?

import pandas as pd
df = pd.DataFrame({"a": [1, 2], "b": [3, 4]})
print(df[["a"]].shape)

A. (2,) B. (1, 2) C. (2, 1) D. (4, 1) Correct answer: C. 6. What is the result?

import pandas as pd
s = pd.Series([1, 2, 3])
print(s > 1)

A. [False, True, True] B. Series of booleans C. ndarray of booleans D. True Correct answer: B. 7. What does this code produce?

import pandas as pd
s = pd.Series([1, 2, 3])
print(s[s > 1])

A. Series [2, 3] B. Series [False, True, True] C. [2, 3] D. IndexError Correct answer: A. 8. What is the output?

import pandas as pd
df = pd.DataFrame({"a": [1, 2], "b": [3, 4]})
print(df.iloc[0, 1])

A. 1 B. 2 C. 3 D. 4 Correct answer: C. 9. What does this select?

df.loc[:, "a"]

A. First row B. First column as Series C. First column as DataFrame D. Entire DataFrame Correct answer: B. 10. What will this code output?

import pandas as pd
df = pd.DataFrame({"a": [1, 2, 3]})
print(len(df))

A. 1 B. 2 C. 3 D. Error Correct answer: C. 11. What is returned?

df.values

A. Series B. DataFrame C. NumPy ndarray D. list Correct answer: C. 12. What does this code output?

import pandas as pd
df = pd.DataFrame({"a": [1, 2, 3]})
print(df.index)

A. [0, 1, 2] B. list C. RangeIndex D. ndarray Correct answer: C. 13. What is the result?

df.columns

A. list B. Series C. Index D. dict Correct answer: C. 14. What does this return?

df.dtypes

A. dict B. Series C. DataFrame D. ndarray Correct answer: B. 15. What is printed?

import pandas as pd
s = pd.Series([1, None, 3])
print(s.isna().sum())

A. 0 B. 1 C. 2 D. 3 Correct answer: B. 16. What does this code output?

import pandas as pd
s = pd.Series([1, None, 3])
print(s.dropna().values)

A. [1, None, 3] B. [None] C. [1, 3] D. Error Correct answer: C. 17. What does this expression return?

df.head(1)

A. First column B. First row as Series C. First row as DataFrame D. Entire DataFrame Correct answer: C. 18. What is the output?

import pandas as pd
df = pd.DataFrame({"a": [1, 2, 3]})
print(df.tail(1)["a"].iloc[0])

A. 1 B. 2 C. 3 D. Error Correct answer: C. 19. What happens here?

df["c"] = df["a"] * 2

A. Raises KeyError B. Modifies column a C. Adds new column c D. No effect Correct answer: C. 20. What does this code output?

import pandas as pd
df = pd.DataFrame({"a": [1, 2, 3]})
print(df.sum().iloc[0])

A. 1 B. 3 C. 6 D. Error Correct answer: C. 21. What does df.mean() return? A. scalar B. Series C. DataFrame D. ndarray Correct answer: B. 22. What is the result?

df["a"].dtype

A. int B. numpy.int64 C. object D. float Correct answer: B. 23. What does this code do?

df = df.rename(columns={"a": "x"})

A. Renames index B. Renames column a to x C. Deletes column a D. Copies DataFrame only Correct answer: B. 24. What does this expression return?

df.loc[df["a"] > 1, :]

A. Boolean Series B. Filtered DataFrame C. Filtered Series D. Error Correct answer: B. 25. What is printed?

import pandas as pd
df = pd.DataFrame({"a": [1, 2, 3]})
print(df.empty)

A. True B. False C. None D. Error Correct answer: B. https://t.me/DataAnalyticsX 😱