What are Python pandas equivalents for R functions like str(), summary(), and head()?
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 890Data columns (total 12 columns):PassengerId 891 non-null int64Survived 891 non-null int64Pclass 891 non-null int64Name 891 non-null objectSex 891 non-null objectAge 714 non-null float64SibSp 891 non-null int64Parch 891 non-null int64Ticket 891 non-null objectFare 891 non-null float64Cabin 204 non-null objectEmbarked 889 non-null objectdtypes: 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)