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Python practice problems help beginners to become experts in a python programming language with a small amount of practice effort.
Write a pandas program to select all columns except one.
name salary 0 Alex 50000 1 John 65000
drop(columns=...).import pandas as pddf = pd.DataFrame({"name": ["Alex", "John"], "age": [30, 27], "salary": [50000, 65000]})print(df.drop(columns="age"))name salary 0 Alex 50000 1 John 65000
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Write a pandas program to find the position of a column.
2
df.columns.get_loc("col").import pandas as pddf = pd.DataFrame({"sr_no": [1], "name": ["Alex"], "age": [30], "salary": [50000]})print(df.columns.get_loc("age"))2
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Write a pandas program to convert a list of lists into a DataFrame.
[["Virat", "cricket"], ["Messi", "football"]]
name sport 0 Virat cricket 1 Messi football
columns=.import pandas as pdprint(pd.DataFrame([["Virat", "cricket"], ["Messi", "football"]], columns=["name", "sport"]))name sport 0 Virat cricket 1 Messi football
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Write a pandas program to get the data type of each column.
name str age int64 salary float64 dtype: object
dtypes.import pandas as pddf = pd.DataFrame({"name": ["Alex", "John"], "age": [30, 27], "salary": [50000.0, 65000.5]})print(df.dtypes)name str age int64 salary float64 dtype: object
pandas 3 shows text columns as str; older versions show object.
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Write a pandas program to check whether a column exists.
True False
"col" in df.columns.import pandas as pddf = pd.DataFrame({"name": ["Alex"], "salary": [50000]})print("salary" in df.columns, "bonus" in df.columns)True False
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Write a pandas program to find the row where a column is smallest.
name Alex salary 50000 Name: 0, dtype: object
idxmin().import pandas as pddf = pd.DataFrame({"name": ["Alex", "John", "Peter", "Klaus"], "salary": [50000, 65000, 63000, 59000]})print(df.loc[df["salary"].idxmin()])name Alex salary 50000 Name: 0, dtype: object
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Write a pandas program to find the row where a column is largest.
name John salary 65000 Name: 1, dtype: object
df.loc[df["salary"].idxmax()].import pandas as pddf = pd.DataFrame({"name": ["Alex", "John", "Peter", "Klaus"], "salary": [50000, 65000, 63000, 59000]})print(df.loc[df["salary"].idxmax()])name John salary 65000 Name: 1, dtype: object
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Write a pandas program to get the values of a column as a list.
['Alex', 'John', 'Peter']
df["col"].tolist().import pandas as pddf = pd.DataFrame({"name": ["Alex", "John", "Peter"], "salary": [50000, 65000, 63000]})print(df["name"].tolist())['Alex', 'John', 'Peter']
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Write a pandas program to rename one column.
Sr.no name 0 1 Alex 1 2 John
rename(columns={"old": "new"}).import pandas as pddf = pd.DataFrame({"Rank": [1, 2], "name": ["Alex", "John"]})print(df.rename(columns={"Rank": "Sr.no"}))Sr.no name 0 1 Alex 1 2 John
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Write a pandas program to shuffle rows.
name age 3 Klaus 33 1 John 27 0 Alex 30 2 Peter 29
sample(frac=1); seed with random_state.import pandas as pddf = pd.DataFrame({"name": ["Alex", "John", "Peter", "Klaus"], "age": [30, 27, 29, 33]})print(df.sample(frac=1, random_state=3))name age 3 Klaus 33 1 John 27 0 Alex 30 2 Peter 29
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