a) Trueb) False Answer: aExplanation: Non-numeric columns will be automatically excluded from the correlation calculation.
View QuestionWhich of the following can potentially change the dtype of a series?
a) reindex_likeb) index_likec) itime_liked) none of the mentioned Answer: aExplanation: reindex_like silently inserts NaNs and ...
View QuestionWhich of the following method produces a data ranking with ties being assigned the mean of the ranks for the group?
a) rankb) dense_rankc) partition_rankd) none of the mentioned Answer: aExplanation: rank is also a DataFrame ...
View Questionrolling_count function gives the number of non-null observations.
a) Trueb) False Answer: bExplanation: The binary operators take two Series or DataFrames.
View QuestionWhich of the following is implemented on DataFrame to compute the correlation between like-labeled Series contained in different DataFrame objects?
a) corrwithb) corwithc) corwitd) none of the mentioned Answer: aExplanation: A score close to 1 ...
View QuestionPoint out the wrong statement.
a) lxml is very fastb) lxml requires Cython to install correctlyc) lxml does not make any guarantees about ...
View QuestionWhich of the following specifies the required minimum number of observations for each column pair in order to have a valid result?
a) min_periodsb) max_periodsc) minimum_periodsd) all of the mentioned Answer: aExplanation: DataFrame.cov also supports an optional ...
View QuestionWhich of the following object has a method cov to compute covariance between series?
a) Seriesb) DataFramec) Paneld) none of the mentioned Answer: aExplanation: DataFrame has a method cov ...
View QuestionPoint out the correct statement.
a) Pandas represents timestamps in microsecond resolutionb) Pandas is 100% thread safec) For Series and DataFrame objects, var ...
View QuestionWhich of the following is used to compute the percent change over a given number of periods?
a) pct_changeb) percent_changec) per_changed) none of the mentioned Answer: aExplanation: Series, DataFrame, and Panel all ...
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