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I'm only aware of the describe() function. Are there any other functions similar to str(), summary(), and head()?
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There are clear points of similarity between both R and Python (pandas Dataframes were inspired by R dataframes, the rvest package was inspired by BeautifulSoup), and both ecosystems continue to grow stronger. In fact, it's remarkable how similar the syntax and approaches are for many common tasks in both languages.
Python str() Function The str() function converts the specified value into a string.
head() returns the first n rows(observe the index values). The default number of elements to display is five, but you may pass a custom number. tail() returns the last n rows(observe the index values).
In pandas the info() method creates a very similar output like R's str():
> str(train) 'data.frame': 891 obs. of 13 variables: $ PassengerId: int 1 2 3 4 5 6 7 8 9 10 ... $ Survived : int 0 1 1 1 0 0 0 0 1 1 ... $ Pclass : int 3 1 3 1 3 3 1 3 3 2 ... $ Name : Factor w/ 891 levels "Abbing, Mr. Anthony",..: 109 191 358 277 16 559 520 629 417 581 ... $ Sex : Factor w/ 2 levels "female","male": 2 1 1 1 2 2 2 2 1 1 ... $ Age : num 22 38 26 35 35 NA 54 2 27 14 ... $ SibSp : int 1 1 0 1 0 0 0 3 0 1 ... $ Parch : int 0 0 0 0 0 0 0 1 2 0 ... $ Ticket : Factor w/ 681 levels "110152","110413",..: 524 597 670 50 473 276 86 396 345 133 ... $ Fare : num 7.25 71.28 7.92 53.1 8.05 ... $ Cabin : Factor w/ 148 levels "","A10","A14",..: 1 83 1 57 1 1 131 1 1 1 ... $ Embarked : Factor w/ 4 levels "","C","Q","S": 4 2 4 4 4 3 4 4 4 2 ... $ Child : num 0 0 0 0 0 NA 0 1 0 1 ... train.info() <class 'pandas.core.frame.DataFrame'> RangeIndex: 891 entries, 0 to 890 Data columns (total 12 columns): PassengerId 891 non-null int64 Survived 891 non-null int64 Pclass 891 non-null int64 Name 891 non-null object Sex 891 non-null object Age 714 non-null float64 SibSp 891 non-null int64 Parch 891 non-null int64 Ticket 891 non-null object Fare 891 non-null float64 Cabin 204 non-null object Embarked 889 non-null object dtypes: float64(2), int64(5), object(5) memory usage: 83.6+ KB This provides output similar to R's str(). It presents unique values instead of initial values.
def rstr(df): return df.shape, df.apply(lambda x: [x.unique()]) print(rstr(iris)) ((150, 5), sepal_length [[5.1, 4.9, 4.7, 4.6, 5.0, 5.4, 4.4, 4.8, 4.3,... sepal_width [[3.5, 3.0, 3.2, 3.1, 3.6, 3.9, 3.4, 2.9, 3.7,... petal_length [[1.4, 1.3, 1.5, 1.7, 1.6, 1.1, 1.2, 1.0, 1.9,... petal_width [[0.2, 0.4, 0.3, 0.1, 0.5, 0.6, 1.4, 1.5, 1.3,... class [[Iris-setosa, Iris-versicolor, Iris-virginica]] dtype: object) If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
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