'Elegant alternative to df[df.columns[0]]
If I want to call the first column of a df without knowing the name of the df, I usually use df[df.columns[0]]. When I use boolean indexing it looks for example like this:
df[df[df.columns[0] > value].count()
Is there a more elegant way to write this? This nesting appears to be very error-prone.
Solution 1:[1]
You can use pandas.DataFrame.iloc to index dataframe based on integer position.
df.iloc[:, 0].gt(value).sum()
Solution 2:[2]
# importing pandas package
import pandas as pd
# making data frame from csv file
data = pd.read_csv("file.csv")
df = pd.DataFrame(data, index = [0, 1, 2, 3, 4, 5, ....])
df[[True, False, True, False, True, False ...]]
Sources
This article follows the attribution requirements of Stack Overflow and is licensed under CC BY-SA 3.0.
Source: Stack Overflow
| Solution | Source |
|---|---|
| Solution 1 | Ynjxsjmh |
| Solution 2 |
