Improved tasks 2877-2891

Author: javadev

src/main/java/g2801_2900/s2877_create_a_dataframe_from_list/solution.py

@@ -4,5 +4,5 @@
 
 def createDataframe(student_data: List[List[int]]) -> pd.DataFrame:
     column_name = ['student_id','age']
-    result = pd.DataFrame(student_data,columns =column_name)
+    result = pd.DataFrame(student_data, columns=column_name)
     return result

src/main/java/g2801_2900/s2878_get_the_size_of_a_dataframe/solution.py

@@ -3,4 +3,4 @@
 import pandas as pd
 
 def getDataframeSize(players: pd.DataFrame) -> List[int]:
-    return[players.shape[0],players.shape[1]]
+    return[players.shape[0], players.shape[1]]

src/main/java/g2801_2900/s2879_display_the_first_three_rows/solution.py

@@ -4,4 +4,3 @@
 
 def selectFirstRows(zs: pd.DataFrame) -> pd.DataFrame:
     return zs.head(3)
-    

src/main/java/g2801_2900/s2880_select_data/solution.py

@@ -4,4 +4,3 @@
 
 def selectData(students: pd.DataFrame) -> pd.DataFrame:
     return students[students.student_id == 101][['name','age']]
-

src/main/java/g2801_2900/s2881_create_a_new_column/solution.py

@@ -3,5 +3,5 @@
 import pandas as pd
 
 def createBonusColumn(employees: pd.DataFrame) -> pd.DataFrame:
-    employees["bonus"] = employees["salary"]*2
+    employees["bonus"] = employees["salary"] * 2
     return employees

src/main/java/g2801_2900/s2883_drop_missing_data/solution.py

@@ -3,6 +3,6 @@
 import pandas as pd
 
 def dropMissingData(students: pd.DataFrame) -> pd.DataFrame:
-   r=pd.DataFrame(students)
-   r.dropna(subset='name',inplace = True)
+   r = pd.DataFrame(students)
+   r.dropna(subset='name', inplace=True)
    return r

src/main/java/g2801_2900/s2889_reshape_data_pivot/solution.py

@@ -3,4 +3,4 @@
 import pandas as pd
 
 def pivotTable(weather: pd.DataFrame) -> pd.DataFrame:
-    return weather.pivot(index='month',columns='city',values='temperature')
+    return weather.pivot(index='month', columns='city', values='temperature')

src/main/java/g2801_2900/s2891_method_chaining/solution.py

@@ -3,12 +3,12 @@
 import pandas as pd
 
 def findHeavyAnimals(animals: pd.DataFrame) -> pd.DataFrame:
-	animal_data = {}
-	for index in animals.index:
-		animal = animals.iloc[index]
-		if animal['weight'] > 100:
-			animal_data[animal['name']] = animal['weight']
+    animal_data = {}
+    for index in animals.index:
+        animal = animals.iloc[index]
+        if animal['weight'] > 100:
+            animal_data[animal['name']] = animal['weight']
 
-	animal_data = dict(sorted(animal_data.items() , key = lambda x : x[1] , reverse = True))
-	result = pd.DataFrame(animal_data.keys() , columns = ['name'])
-	return result
+    animal_data = dict(sorted(animal_data.items() , key = lambda x : x[1] , reverse = True))
+    result = pd.DataFrame(animal_data.keys() , columns = ['name'])
+    return result