Pandas cheat sheet

gistfile1.md

The pandas equivalent to...

select * from table where column_name = some_value

is:

table[table.column_name == some_value]

Multiple conditions:

table[(table.column_name == some_value) | (table.column_name2 == some_value2)]

or...

table.query('column_name == some_value | column_name2 == some_value2')

###Code example import pandas as pd

###Create data set d = {'foo':[100, 111, 222], 'bar':[333, 444, 555]} df = pd.DataFrame(d)

###Full dataframe: df

###Shows: #|bar|foo ==|==|== 0|333|100 1|444|111 2|555|222

Output only the row(s) in df where foo is 222:

df[df.foo == 222]

Shows:

bar foo

2 555 222

In the above code it is the line df[df.foo == 222] that gives the rows based on the column value, 222 in this case.

Multiple conditions are also possible:

df[(df.foo == 222) | (df.bar == 444)]

bar foo

1 444 111

2 555 222

But at that point I would recommend using the query function, since it's less verbose and yields the same result:

df.query('foo == 222 | bar == 444')

gistfile1.txt

#md 

tl;dr
The pandas equivalent to

`select * from table where column_name = some_value`
is

table[table.column_name == some_value]
Multiple conditions:

table[(table.column_name == some_value) | (table.column_name2 == some_value2)]
or

table.query('column_name == some_value | column_name2 == some_value2')
Code example
import pandas as pd

# Create data set
d = {'foo':[100, 111, 222], 
     'bar':[333, 444, 555]}
df = pd.DataFrame(d)

# Full dataframe:
df

# Shows:
#    bar   foo 
# 0  333   100
# 1  444   111
# 2  555   222

# Output only the row(s) in df where foo is 222:
df[df.foo == 222]

# Shows:
#    bar  foo
# 2  555  222
In the above code it is the line df[df.foo == 222] that gives the rows based on the column value, 222 in this case.

Multiple conditions are also possible:

df[(df.foo == 222) | (df.bar == 444)]
#    bar  foo
# 1  444  111
# 2  555  222
But at that point I would recommend using the query function, since it's less verbose and yields the same result:

df.query('foo == 222 | bar == 444')