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pandas sort columns by name
df = df.reindex(sorted(df.columns), axis=1)
dataframe sort by column
sorted = df.sort_values('column-to-sort-on', ascending=False)
#or
df.sort_values('name', inplace=True)
dataframe, sort by columns
final_df = df.sort_values(by=['2'], ascending=False)
sort df by column
df.rename(columns={1:'month'},inplace=True)
df['month'] = pd.Categorical(df['month'],categories=['December','November','October','September','August','July','June','May','April','March','February','January'],ordered=True)
df = df.sort_values('month',ascending=False)
pandas sort by columns
# Python, Pandas
# Sorting dataframe
# sort by one column
df.sort_values(by=['col1'])
# sort by more columns
df.sort_values(by=['col1', 'col2'])
# defaut values
# DataFrame.sort_values(by, axis=0, ascending=True, inplace=False, kind='quicksort', na_position='last', ignore_index=False, key=None)
Sorting Dataframes by Column Python Pandas
# Sorting Pandas Dataframe in Descending Order
# importing pandas library
import pandas as pd
# Initializing the nested list with Data set
age_list = [['Afghanistan', 1952, 8425333, 'Asia'],
['Australia', 1957, 9712569, 'Oceania'],
['Brazil', 1962, 76039390, 'Americas'],
['China', 1957, 637408000, 'Asia'],
['France', 1957, 44310863, 'Europe'],
['India', 1952, 3.72e+08, 'Asia'],
['United States', 1957, 171984000, 'Americas']]
# creating a pandas dataframe
df = pd.DataFrame(age_list, columns=['Country', 'Year',
'Population', 'Continent'])
# Sorting by column "Population"
df.sort_values(by=['Population'], ascending=False)
sort columns dataframe
df = df.reindex(sorted(df.columns), axis=1)
pandas sort dataframe by column
# Basic syntax:
import pandas as pd
df.sort_values(by=['col1'])
# Note, this does not sort in place unless you add inplace=True
# Note, add ascending=False if you want to sort in decreasing order
# Note, to sort by more than one column, add other column names to the
# list like by=['col1', 'col2']
pandas head sort by colun name
DataFrame.sort_values(
['column_to_sort_by'],
axis=0,
ascending=True,
inplace=False,
kind='quicksort',
na_position='last',
ignore_index=False,
key=None
)
pandas dataframe sort by column
df.sort_values(by=['col1])
df sort by column names
python dataframe sort by column name
>>> result = df.sort(['A', 'B'], ascending=[1, 0])
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