Pandas DataFrame loc Property
Example
Return the age of Mary:
import pandas as pd
data =
[[50, True], [40, False], [30, False]]
label_rows = ["Sally", "Mary", "John"]
label_cols = ["age", "qualified"]
df = pd.DataFrame(data,
label_rows, label_cols)
print(df.loc["Mary",
"age"])
Try it Yourself »
Definition and Usage
The loc property gets, or sets, the value(s) of
the specified labels.
Specify both row and column with a label.
To access more than one row, use double brackets and specify the labels, separated by commas:
df.loc[["Sally", "John"]]
Specify columns by including their labels in another list:
df.loc[["Sally", "John"], ["age",
"qualified"]]
You can also specify a slice of the DataFrame with from and to labels, separated by a colon:
df.loc["Sally": "John"]
Note: When slicing, both from and to are included in the result.
Syntax
dataframe.loc[row, column)
Parameters
| Parameter | Description |
|---|---|
| row | Optional. A label, or labels, specifying the label of the row(s)
|
| column | Optional. A label, or labels, specifying the label of the column(s)
|
Return Value
Depends on the input:
Single labels for both row and column ["Sally", "age"] returns the content of that cell.
Single label for one row ["Sally"] returns a
Pandas Series.
A list of labels [["Sally", "Mary"]] returns a
Pandas DataFrame.
