Pandas

Pandas is a fast, powerful, flexible and easy to use open source data analysis and manipulation tool, built on top of the Python programming language.

Install⚑

pip3 install pandas

Import

import pandas as pd

Snippets⚑

Load csv ⚑

data = pd.read_csv("filename.csv")

If you want to parse the dates of the start column give read_csv the argument parse_dates=['start'].

Do operation on column data and save it in other column ⚑

# make a simple dataframe
df = pd.DataFrame({'a':[1,2], 'b':[3,4]})
df
#    a  b
# 0  1  3
# 1  2  4

# create an unattached column with an index
df.apply(lambda row: row.a + row.b, axis=1)
# 0    4
# 1    6

# do same but attach it to the dataframe
df['c'] = df.apply(lambda row: row.a + row.b, axis=1)
df
#    a  b  c
# 0  1  3  4
# 1  2  4  6

Get unique values of column ⚑

If we want to get the unique values of the name column:

df.name.unique()

Extract columns of dataframe ⚑

df1 = df[['a','b']]

Remove dumplicate rows ⚑

df = df.drop_duplicates()

Remove column from dataframe ⚑

del df['name']

Count unique combinations of values in selected columns ⚑

df1.groupby(['A','B']).size().reset_index().rename(columns={0:'count'})

     A    B  count
0   no   no      1
1   no  yes      2
2  yes   no      4
3  yes  yes      3

Get row that contains the maximum value of a column ⚑

df.loc[df['Value'].idxmax()]

References⚑

Homepage