Pandy dodają ramkę danych na dno innego
# Basic syntax:
new_dataframe = old_dataframe.filter(['Columns','you','want'], axis=1)
Charles-Alexandre Roy
# Basic syntax:
new_dataframe = old_dataframe.filter(['Columns','you','want'], axis=1)# Short answer:
# Adjust the bandwidth parameter to smaller values. E.g. bw = 0.1
# Example usage:
import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
data = np.random.rand(100)
sns.violinplot(y=data, bw=0.1) # Changing the bw parameter adjusts how
# tightly the data is fit by the kernel density estimate (KDE)# Basic syntax:
which(is.na(your_dataframe), arr.ind=TRUE)
# Where:
# - which returns the dataframe row indices for rows that contain
# a logical of TRUE
# - is.na processes the dataframe and converts all values to TRUE or
# FALSE based on whether they are NA or not# Basic syntax:
your_dataframe[row_number, column_number] = new_value# Basic syntax (use index = False):
df.to_string(index = False)df = df.append({'index1': value1, 'index2':value2,...}, ignore_index=True)