PYTHON

get list of column names pandas

col_names = list(df.columns)

get a list of column names pandas

lists = data.columns.to_list()

python return column names of pandas dataframe

# Basic syntax:
your_dataframe.columns

# Note, if you want the column names as a list, just do:
list(your_dataframe.columns)

create dataframe with column names pandas

In [4]: import pandas as pd
In [5]: df = pd.DataFrame(columns=['A','B','C','D','E','F','G'])
In [6]: df
Out[6]:
Empty DataFrame
Columns: [A, B, C, D, E, F, G]
Index: []

pd dataframe get column names

lst = data.columns.values     # data is dataframe

pandas dataframe column names

print(data.columns.values)

Getting the column names as list

# 5. Getting column names
df.columns.tolist()

python pandas give column names

# adding column name to the respective columns
df.columns =['Name', 'Code', 'Age', 'Weight']
  
# displaying the DataFrame
print(df)

get dataframe column names

# Import pandas package 
import pandas as pd 
    
# making data frame 
data = pd.read_csv("nba.csv") 
  
# iterating the columns
for col in data.columns:
    print(col)

name columns pandas

df.columns = ['column1', 'column2', 'column3']
df.columns

changing names of column pandas

import pandas as pd

# You don't need these two lines
# as you already have your DataFrame in memory
df = pd.read_csv("nor.txt", sep="|")
df.drop(df.columns[-1], axis=1)

# Get column names
cols = df.columns

# Create a new DataFrame with just the markdown
# strings
df2 = pd.DataFrame([['---',]*len(cols)], columns=cols)

#Create a new concatenated DataFrame
df3 = pd.concat([df2, df])

#Save as markdown
df3.to_csv("nor.md", sep="|", index=False)

name columns pandas

>gapminder.columns = ['country','year','population',
                     'continent','life_exp','gdp_per_cap']

dataframe names pandas

print(df.rename(columns={'A': 'a', 'C': 'c'}))