Pandas

Question 1

Create a new DataFrame

Answer 1

df = pd.DataFrame() (Atenção com as maiúsculas!)

Question 2

parâmetro axis=0

Answer 2

eixo x

Question 3

parâmetro axis=1

Answer 3

eixo y

Question 4

selecionar colunas W e Z do dataframe

Answer 4

df[[‘W’,’Z’]]

Question 5

cria coluna nova no dataframe

Answer 5

df[‘new’] = df[‘W’] + df[‘Y’]

Question 6

Algo to cut the lines of the DataFrame up to a value

Answer 6

Find the line index using line= df.loc[df[‘COL’] == ‘Limite’].index.min()

df = df[df.index < line]

Question 7

Cut the columns on a DataFrame

Answer 7

col_names = [‘Data’, ‘A’]

df = df[col_names]

Question 8

Caps Lock no nome das colunas

Answer 8

df.columns = df.columns.str.upper()

Question 9

Substituir nan em uma coluna por um valor

Answer 9

df[‘A’] = df[‘A’].fillna(‘0,0’)

Question 10

aplicar uma funcao em uma serie

Answer 10

df[‘A’] = df[‘A’].apply(function)

Question 11

change a DataFrame column from string to date

Answer 11

import datetime

df[‘A’] = pd.to_datetime(df[‘A’], format=’%d/%m/%y’)

Question 12

truncate (cut) values on a column

Answer 12

df[‘A’] = df[‘A’].map(str).str.slice(0,10)

Question 13

consolida dataframes em um dataframe final

Answer 13

df_final.append(df_bradesco)
df_final = pd.concat(df_final, axis=0)

Question 14

transforma uma coluna para o tipo string

Answer 14

df[‘A’].astype(str)

Question 15

remover duplicatas de um dataframe

Answer 15

df.drop_duplicates(inplace=True)

Question 16

left join de dois dataframes

Answer 16

df_final = pd.merge(df_final,df_teste,how=’left’,left_on=’KEY’,right_on=’KEY’)

Question 17

para cada linha da serie, recebe um valor de outra serie

Answer 17

df.at[chave_base, ‘A’] = df_teste.at[chave_teste, ‘A’]

Question 18

Saving DataFrames to an Excel Workbook

Answer 18

from pandas import ExcelWriter

writer = ExcelWriter(‘filename.xlsx’)

df1. to_excel(writer, ‘Sheet1’)
writer. save()

Question 19

Save DataFrame as a dictionary

Answer 19

d = df.to_dict()

Question 20

Save DataFrame as a string

Answer 20

str = df.to_string()

Question 21

Save DataFrame as a numpy matrix

Answer 21

m = df.to_matrix()

Question 22

Transpose rows and columns in a DataFrame

Answer 22

df = df.T

Question 23

Iterate between columns

Answer 23

df.iteritems()

Question 24

Iterate between rows

Answer 24

df.iterrows()

Question 25

Filter a DataFrame with like

Answer 25

df = df.filter(like=’x’)

Question 26

Get first column label in a DataFrame

Answer 26

label = df.columns[0]

Question 27

Get list of column labels in a DataFrame

Answer 27

lis = df.columns.tolist()

Question 28

Get an array of column labels in a DataFrame

Answer 28

a = df.columns.values

Question 29

Select column to series

Answer 29

s= df[‘colName’]

Question 30

Select column to DataFrame

Answer 30

df = df[[‘colName] ]

Question 31

Select all but last column to a DataFrame

Answer 31

df = df[df.columns[:-1] ]

Question 32

Swap columns content in a DataFrame

Answer 32

df[[‘B’, ‘A’] ] = df[[‘A’, ‘B’] ]

Question 33

Dropping (deleting) columns

Answer 33

df.drop(‘col1’, axis=1, inplace=True)

Question 34

Apply log to a column

Answer 34

df[‘log_data’] = np.log( df[‘col1’] )

Question 35

Set column values based on criteria

Answer 35

df]’d’] = df[‘a].where(df.b != 0, other=df.c)

Question 36

Find index label for min/max values in column

Answer 36

label = df[‘col1’].idxmin()

label = df[‘col1’].idxmax()

Question 37

Module of a column in a DataFrame

Answer 37

df[‘col’] = df[‘col’].abs()

Question 38

Convert column to date

Answer 38

s = df[‘col’],to_datetime()

Question 39

Create a column with a rolling pct change

Answer 39

s = df[‘col’].pct_change(periods=4)

Question 40

Create a column with a rolling calculation

Answer 40

s = df[‘col’].rolling(window=4, min_periods=4, center=False).sum()

Question 41

Append a column of row sums in a DataFrame

Answer 41

df[‘Total’] = df.sum(axis=1)

Question 42

Get the integer position of a column index label

Answer 42

i = df.columns.get_loc(‘col_name’)

Question 43

Adding rows to a DataFrame

Answer 43

df = original_df.append(more_rows_in_df)

Question 44

Dropping rows (by name)

Answer 44

df = df.drop(‘row_label’)

Question 45

Boolean row selection by values greater than

Answer 45

df = df[df[‘col2’] >= 0.0]

Question 46

Boolean row selection by values with OR condition

Answer 46

df = df[(df[‘col3’] >= 0.0) | (df[‘col1’] < 0.0)

need parenthesis around comparisons

Question 47

Boolean row selection by values in list

Answer 47

df = df[df[‘col’].isin( [1, 2, 5, 7, 11] ) ]

Question 48

Boolean row selection by values NOT in list

Answer 48

df = df[~ df[‘col’].isin( [1, 2, 5, 7, 11] ) ]

Question 49

Boolean row selection by values containing

Answer 49

df = df[df[‘col’].str.contains(‘hello’) ]

Question 50

Get integer position of rows that meet condition

Answer 50

a = np.where(df[‘col’] >= 2)

produces a numpy array

Question 51

Find row index duplicates

Answer 51

if df.items.has_duplicates:

prin(df.index.duplicated() )

Question 52

Select a cell by row and column labels

Answer 52

value = df.at[‘row’, ‘col’]

.at[] is the fastest label based scalar lookup

Question 53

Grouping with an aggregating function

Answer 53

s = df.groupby(‘cat’)[‘col1’].sum()

Question 54

Change a string to lower case

Answer 54

s = df[‘col’].str.lower()

Question 55

Get the length of the strings in a column

Answer 55

s =df[‘col’].str.len()

Question 56

Append values to a string

Answer 56

df[‘col’] += ‘suffix’

Question 57

Filter a DataFrame with a list of items

Answer 57

df = df.filter(items[‘a’ , ‘b’], axis=0)

Question 58

Remove lines with NaN

Answer 58

df.dropna(inplace=True)

Question 59

Definition of the Strip method for strings

Answer 59

Returns a copy of the string with both leading and trailing characters removed (based on the string argument passed).