sort dataframe by column
df.sort_values(by='col1', ascending=False)sort dataframe by column
df.sort_values(by='col1', ascending=False)sorting by column in pandas
# Python, Pandas
# Sorting dataframe df on the values of a column col1
# Return sorted array without modifying the original one
df.sort_values(by=["col1"])
# Sort the original array permanently
df.sort_values(by=["col1"], inplace = True)pandas reorder columns
# setting up a dummy dataframe
raw_data = {'name': ['Willard Morris', 'Al Jennings', 'Omar Mullins', 'Spencer McDaniel'],
'age': [20, 19, 22, 21],
'favorite_color': ['blue', 'red', 'yellow', "green"],
'grade': [88, 92, 95, 70]}
df = pd.DataFrame(raw_data, index = ['Willard Morris', 'Al Jennings', 'Omar Mullins', 'Spencer McDaniel'])
df
#now 'age' will appear at the end of our df
df = df[['favorite_color','grade','name','age']]
df.head()python more order of columns
In [7]: cols = df.columns.tolist()
In [8]: cols
Out[8]: [0L, 1L, 2L, 3L, 4L, 'mean']
In [12]: cols = cols[-1:] + cols[:-1]
In [13]: cols
Out[13]: ['mean', 0L, 1L, 2L, 3L, 4L]
In [14]: df = df[cols]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 order dataframe by column of other dataframe
df1 = df1.set_index('column_in_df1')
df1 = df1.reindex(index=df2['column_in_df2'])
df1 = df1.reset_index()Copyright © 2021 Codeinu
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