Pandas

0 / 160 solved · Easy 55 · Medium 85 · Hard 20

#		Title	Difficulty
1	○	Import pandas	Easy
2	○	pandas Version	Easy
3	○	Create a DataFrame	Easy
4	○	Summary of a DataFrame	Easy
5	○	First 3 Rows	Easy
6	○	Select Two Columns	Easy
7	○	Select Rows and Columns	Easy
8	○	Rows with Visits > 3	Easy
9	○	Rows with Missing Age	Easy
10	○	Cats Younger Than 3	Easy
11	○	Age Between 2 and 4	Easy
12	○	Change a Single Value	Easy
13	○	Total Visits	Easy
14	○	Mean Age per Animal	Easy
15	○	Append then Delete a Row	Easy
16	○	Count Each Animal	Easy
17	○	Sort by Two Columns	Easy
18	○	Map yes/no to Boolean	Easy
19	○	Replace a Value	Easy
20	○	Pivot Table of Mean Age	Medium
21	○	Drop Consecutive Duplicates	Medium
22	○	Subtract the Row Mean	Medium
23	○	Column with Smallest Sum	Medium
24	○	Count Fully-Unique Rows	Medium
25	○	Column of the Third NaN	Hard
26	○	Sum of Three Greatest per Group	Hard
27	○	Sum over Integer Bins	Hard
28	○	Distance to Previous Zero	Hard
29	○	Locations of 3 Largest Values	Hard
30	○	Patch Negatives with Group Mean	Hard
31	○	Grouped Rolling Mean (ignore NaN)	Hard
32	○	Business-Day Series of 2015	Easy
33	○	Sum on Wednesdays	Medium
34	○	Mean per Calendar Month	Medium
35	○	Peak Date per 4 Months	Hard
36	○	Third Thursdays	Medium
37	○	Fill Missing Flight Numbers	Medium
38	○	Split From_To Column	Medium
39	○	Standardise City Capitalisation	Medium
40	○	Replace Column with Split Columns	Medium
41	○	Extract Airline Name	Medium
42	○	Expand List Column	Medium
43	○	Build a MultiIndex Series	Medium
44	○	Is the Index Sorted?	Medium
45	○	Select from Second Level	Medium
46	○	Slice a MultiIndex	Medium
47	○	Sum per First Level	Medium
48	○	Sum per Second Level via unstack	Medium
49	○	Swap and Sort Index Levels	Medium
50	○	Minesweeper: Grid Coordinates	Medium
51	○	Minesweeper: Place Mines	Medium
52	○	Minesweeper: Adjacent Counts	Hard
53	○	Minesweeper: NaN on Mines	Medium
54	○	Minesweeper: Reshape to Grid	Hard
55	○	Hourly OHLC Aggregation	Medium
56	○	Filter Rows by Membership	Easy
57	○	Reindex Rows and Columns	Medium
58	○	Flag Duplicate Rows by Subset	Medium
59	○	Cross-Section from a MultiIndex	Medium
60	○	Tuple-Index a MultiIndex with .loc	Medium
61	○	Extract One Group	Easy
62	○	Named Aggregations per Group	Medium
63	○	Filter Groups by an Aggregate Condition	Medium
64	○	Within-Group Z-Score	Hard
65	○	Roll to the Nearest Business Day	Medium
66	○	Mean Value in Leap-Year Februaries	Medium
67	○	Resample to a New Frequency with Forward Fill	Medium
68	○	Find the Longest String	Easy
69	○	Concatenate Two String Columns	Easy
70	○	Extract the Last Two Characters	Easy
71	○	Filter Rows Matching a Regex	Medium
72	○	One-Hot Encode a Multi-Value Column	Medium
73	○	Safe Lookup with a Default	Easy
74	○	Add a Prefix to Index Labels	Easy
75	○	Interquartile Range	Easy
76	○	Count Unique Values, Counting NaN	Easy
77	○	Add Two Series with a Fill Value	Medium
78	○	Cast Specific Columns	Easy
79	○	Rename Columns and Index Together	Easy
80	○	Drop Sparse Rows with a Threshold	Medium
81	○	Stack Two DataFrames	Easy
82	○	Concatenate with Hierarchical Keys	Medium
83	○	Concatenate Column-Wise with an Outer Join	Medium
84	○	Inner Merge on a Shared Key	Easy
85	○	Left Merge with Differently-Named Keys	Medium
86	○	Distinct Neighbourhoods	Easy
87	○	Tracks in the Top Ten	Easy
88	○	Cheapest Listing in Each City	Easy
89	○	Salary Against the Department Average	Medium
90	○	City Offering the Most Amenities	Medium
91	○	Average Order Value by Weekday and Hour	Medium
92	○	Month-Over-Month User Growth per Account	Hard
93	○	Score Spread Among Grade-A Inspections	Easy
94	○	Correlation Between Emails and Sessions	Hard
95	○	Longest Winning Streak	Hard
96	○	Job Titles on the Top Salary	Easy
97	○	Rank Senders by Volume	Medium
98	○	Completed Tasks for One Company	Medium
99	○	Distinct Streets per Postal Code	Medium
100	○	Active Three Days Running	Hard
101	○	Dense-Rank Hosts by Total Beds	Medium
102	○	Budget per Assigned Employee	Medium
103	○	Three-Month Rolling Revenue	Hard
104	○	Month-Over-Month Revenue Change	Medium
105	○	One Current Row per Employee	Easy
106	○	Housing Units Completed per Year	Easy
107	○	Rank Guests Oldest First	Easy
108	○	Customers Who Never Ordered	Medium
109	○	Total Order Cost per Customer	Easy
110	○	Users in the Top Distance Ranks	Medium
111	○	Share of Viewed Posts That Are Spam	Medium
112	○	Cities Above the National Average	Medium
113	○	Best Rating per Search	Medium
114	○	Peak Headcount During Each Tenure	Hard
115	○	Missing Email or Under Eighteen	Easy
116	○	Five Highest Salaries, Ties Included	Easy
117	○	Top Three Products in Each Category	Medium
118	○	Second-Highest Distinct Salary per Department	Medium
119	○	Sort by a Custom Priority Order	Medium
120	○	Bucket Salaries into Bands	Easy
121	○	Outliers by the 1.5 IQR Rule	Medium
122	○	Rows Where a Product's Price Changed	Medium
123	○	Distinct Customers per Month	Medium
124	○	Each Product's Share of Its Category	Medium
125	○	Quantity-Weighted Average Price	Medium
126	○	Order Counts Including Customers With None	Easy
127	○	Most Frequently Ordered Product	Medium
128	○	Best-Selling Product in Each Category	Medium
129	○	Running Total per Store	Medium
130	○	Number Each Customer's Orders	Medium
131	○	First Purchase, Last Purchase, Days Between	Medium
132	○	Customers With at Least One Order	Medium
133	○	Reconcile Two Systems	Medium
134	○	Join Three Tables	Medium
135	○	Expand a Many-to-Many Relationship	Medium
136	○	Convert Sales Using a Dated Rate Table	Medium
137	○	Attach the Last Known Price to Each Trade	Hard
138	○	Ids Appearing More Than Once	Medium
139	○	Combine Two Months of Transactions	Easy
140	○	Stack Frames With Different Columns	Medium
141	○	Missing-Value Report	Easy
142	○	Fill Missing Salary With the Department Median	Medium
143	○	Carry Balances Forward Within a Customer	Medium
144	○	First Available Phone Number	Easy
145	○	Find Duplicate Transactions	Medium
146	○	Wide to Long	Easy
147	○	Long to Wide	Medium
148	○	Cross-Tabulate Two Columns	Easy
149	○	Cross-Tabulation as Row Percentages	Medium
150	○	Five Most Common Tags	Easy
151	○	Count Email Domains	Easy
152	○	Tidy Up Names	Easy
153	○	Hashtag Frequencies	Medium
154	○	Most Common Words	Medium
155	○	Strip Phone Numbers to Digits	Medium
156	○	Split a Timestamp into Features	Easy
157	○	Seven-Day Trailing Average per Store	Medium
158	○	Change From the Previous Order	Medium
159	○	Split Events into Sessions	Hard
160	○	Monthly Cohort Retention	Hard