How to Remove Duplicate Rows From a Data Frame in Pandas (Python)
↓ Code Available Below! ↓
This video shows how to remove duplicate rows in pandas data frames. Duplicate rows can exist in data due to erroneous data entry or data manipulations like joins and concatenations and should be corrected before performing analysis. In some cases, duplicated rows might be a legitimate feature of the data, but any data set with a unique row index identifier or key column should not have any duplicate rows. Getting rid of duplicate rows is a common data preprocessing step so this task can be achieved easily on Pandas data frames using the data frame method df.dropduplicates()
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Code used in this Python Code Clip:
import pandas as pd
data = pd.DataFrame({"character": ["Goku","Vegeta", "Nappa","Goku","Piccolo"],
"power level": [12000, 16000, 4000, 12000, 3000]})
data
Use df.drop_duplicates() to remove duplicate rows
data = data.drop_duplicates()
data
** Note: YouTube does not allow greater than or less than symbols in the text description, so the code above will not be exactly the same as the code shown in the video! I will use Unicode large ＜ and ＞ symbols in place of the standard sized ones. .
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