import pandas as pd import numpy as np from pandas import (Series, Index, DataFrame)
df.loc, df.ix, df.iloc --> and how it works with the index
In [2]:
columns = ['id', 'name','color','marbles']
data = [
{'id':0, 'name': 'Fred', 'color':'red', 'marbles':2},
{'id':1, 'name': 'Zhang', 'color':'blue', 'marbles':5},
{'id':2, 'name': 'Deb', 'color':'orange', 'marbles':0}
]
df = DataFrame(data, columns=columns)
df
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Let's keep the index integer (to keep with convention of qgrid)
Can use .loc and an integer not already in the index to insert a row at the end of the DataFrame.
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df.loc[max(df.index) + 1]=[4, 'Andy','cherise',4 ]
# need to let data_widget know to update based on change in df
df
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How to insert a row in an arbitrary position?
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# replaces not inserts
df.iloc[1] = [5, 'Raymond','apple',4 ]
df
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# http://pandas.pydata.org/pandas-docs/version/0.17.1/generated/pandas.DataFrame.reindex.html
new_id = max(df.index) + 1
new_index = list(df.index.copy())
df.loc[new_id]=[4, 'Josh','crab apple',89 ]
# move new_index to row
row = 1
new_index.insert(row,new_id)
df = df.reindex(new_index)
df
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How to insert a row in an arbitrary position
Deleting rows -> by computing the label corresponding to row number...
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# another approach
line = DataFrame([[90, 'Wolfgang','fuji apple',33 ]], columns=columns, index=[3])
df = pd.concat([df.iloc[:2], line, df.iloc[3:]]).reset_index(drop=True)
df
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# removing rows
# http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.drop.html
df = df.drop(df.index[1]).reset_index(drop=True)
df
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In [10]:
# modify
df.loc[1,'name'] = 'Ludwig'
df
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