Manipulasi Data dengan pandas

DasarTingkat Keterampilan

Diperbarui 09/2025

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Deskripsi Kursus

Persyaratan

Intermediate Python

Transforming DataFrames

Let’s master the pandas basics. Learn how to inspect DataFrames and perform fundamental manipulations, including sorting rows, subsetting, and adding new columns.

Introducing DataFrames

50 XP

Inspecting a DataFrame

100 XP

Parts of a DataFrame

100 XP

Sorting and subsetting

50 XP

Sorting rows

100 XP

Subsetting columns

100 XP

Subsetting rows

100 XP

Subsetting rows by categorical variables

100 XP

New columns

50 XP

Adding new columns

100 XP

Combo-attack!

100 XP

Mulai Bab

Aggregating DataFrames

In this chapter, you’ll calculate summary statistics on DataFrame columns, and master grouped summary statistics and pivot tables.

Summary statistics

50 XP

Mean and median

100 XP

Summarizing dates

100 XP

Efficient summaries

100 XP

Cumulative statistics

100 XP

Counting

50 XP

Dropping duplicates

100 XP

Counting categorical variables

100 XP

Grouped summary statistics

50 XP

What percent of sales occurred at each store type?

100 XP

Calculations with .groupby()

100 XP

Multiple grouped summaries

100 XP

Pivot tables

50 XP

Pivoting on one variable

100 XP

Fill in missing values and sum values with pivot tables

100 XP

Mulai Bab

Slicing and Indexing DataFrames

Indexes are supercharged row and column names. Learn how they can be combined with slicing for powerful DataFrame subsetting.

Explicit indexes

50 XP

Setting and removing indexes

100 XP

Subsetting with .loc[]

100 XP

Setting multi-level indexes

100 XP

Sorting by index values

100 XP

Slicing and subsetting with .loc and .iloc

50 XP

Slicing index values

100 XP

Slicing in both directions

100 XP

Slicing time series

100 XP

Subsetting by row/column number

100 XP

Working with pivot tables

50 XP

Pivot temperature by city and year

100 XP

Subsetting pivot tables

100 XP

Calculating on a pivot table

100 XP

Mulai Bab

Creating and Visualizing DataFrames

Learn to visualize the contents of your DataFrames, handle missing data values, and import data from and export data to CSV files.

Visualizing your data

50 XP

Which avocado size is most popular?

100 XP

Changes in sales over time

100 XP

Avocado supply and demand

100 XP

Price of conventional vs. organic avocados

100 XP

Missing values

50 XP

Finding missing values

100 XP

Removing missing values

100 XP

Replacing missing values

100 XP

Creating DataFrames

50 XP

List of dictionaries

100 XP

Dictionary of lists

100 XP

Reading and writing CSVs

50 XP

CSV to DataFrame

100 XP

DataFrame to CSV

100 XP

Wrap-up

50 XP

Mulai Bab

Manipulasi Data dengan pandas

Kursus
Selesai

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Bergabung dengan 19 juta pelajar dan mulai Manipulasi Data dengan pandas Hari Ini!

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Deskripsi Kursus

Memperoleh Surat Keterangan Prestasi

Bergabung dengan .css-nklxlk{color:var(--wf-brand--main, #03EF62);}19 juta pelajar dan mulai Manipulasi Data dengan pandas Hari Ini!

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Bergabung dengan 19 juta pelajar dan mulai Manipulasi Data dengan pandas Hari Ini!