pandas

问题 Recently I started to analyse a data frame and I want to remove all the substrings that don't contain ('Aparelho Celular','Internet (Serviços e Produtos)','Serviços Telefônicos Diversos','Telefonia Celular','Telefonia Comunitária ( PABX, DDR, Etc. )','Telefonia Fixa','TV por Assinatura','Televisão / Aparelho DVD / Filmadora','Telemarketing') But when I use this syntax- df = df[~df["GrupoAssunto"].str.contains('Aparelho Celular','Internet (Serviços e Produtos)','Serviços Telefônicos Diversos',

问题 I am trying to reverse geocode data and for that I have below query import overpy import pandas as pd import numpy as np df = pd.read_csv("/home/runner/sample.csv") df.sort_values(by=['cvdt35_timestamp_s'],inplace=True) api= overpy.Overpass() box = 0.0005 queries = [] results = [] df['Name']='' df['Highway'] ='' with open("sample.csv") as f: for row in df.index: query = 'way('+str(df.gps_lat_dd.iloc[row]-box)+','+str(df.gps_lon_dd.iloc[row]-box)+','+str(df.gps_lat_dd.iloc[row]+box)+','+str(df

问题 I have a pandas dataframe with multiindex as the following: TALLY DAY NODE CLASS 2018-02-04 pdk2r08o005 3 7.0 2018-02-05 pdk2r08o005 3 24.0 2018-02-06 dsvtxvCsdbc02 3 2.0 pdk2r08o005 3 28.0 2018-02-07 pdk2r08o005 3 24.0 2018-02-08 dsvtxvCsdbc02 3 3.0 pdk2r08o005 3 24.0 2018-02-09 pdk2r08o005 3 24.0 2018-02-10 dsvtxvCsdbc02 3 2.0 pdk2r08o005 3 24.0 2018-02-11 pdk2r08o005 3 31.0 2018-02-12 pdk2r08o005 3 24.0 2018-02-13 pdk2r08o005 3 20.0 2018-02-14 dsvtxvCsdbc02 3 4.0 pdk2r08o005 3 24.0 2018-02

问题 I am trying to figure out how could I plot this data: column 1 ['genres']: These are the value counts for all the genres in the table Drama 2453 Comedy 2319 Action 1590 Horror 915 Adventure 586 Thriller 491 Documentary 432 Animation 403 Crime 380 Fantasy 272 Science Fiction 214 Romance 186 Family 144 Mystery 125 Music 100 TV Movie 78 War 59 History 44 Western 42 Foreign 9 Name: genres, dtype: int64 column 2 ['release_year']: These are the value counts for all the release years for different

问题 I have a dataframe like following : <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>Title</th> <th>ASIN</th> <th>State</th> <th>SellerSKU</th> <th>Quantity</th> <th>FBAStock</th> <th>QuantityToShip</th> </tr> </thead> <tbody> <tr> <th>1</th> <td>Daedal crafters- Pack of Two Gajra (Orange and...</td> <td>B075T64ZWJ</td> <td>WEST BENGAL</td> <td>DC216</td> <td>1</td> <td>0</td> <td>1</td> </tr> <tr> <th>2</th> <td>Daedal Dream Catchers - Intricate Web

问题 Trying to implement pandas.read_sql function. I created a clickhouse table and filled it: create table regions ( date DateTime Default now(), region String ) engine = MergeTree() PARTITION BY toYYYYMM(date) ORDER BY tuple() SETTINGS index_granularity = 8192; insert into regions (region) values ('Asia'), ('Europe') Then python code: import pandas as pd from sqlalchemy import create_engine uri = 'clickhouse://default:@localhost/default' engine = create_engine(uri) query = 'select * from regions

问题 I am looking for a way to imitate the hist method of pandas.DataFrame using plotly. Here's an example using the hist method: import seaborn as sns import matplotlib.pyplot as plt # load example data set iris = sns.load_dataset('iris') # plot distributions of all continuous variables iris.drop('species',inplace=True,axis=1) iris.hist() plt.tight_layout() which produces: How would one do this using plotly? 回答1: Plotly has a histogram function built in so all you have to do is write px.histogram

问题 How does the following filter out the results in pandas ? For example, with this statement: df[['name', 'id', 'group']][df.id.notnull()] I get 426 rows (it filters out everything where df.group IS NOT NULL ). However, if I just use that syntax by itself, it returns a bool for each row, {index: bool }: [df.group.notnull()] How does the bracket notation work with pandas ? Another example would be: df.id[df.id==458514] # filters out rows # vs [df.id==458514] # returns a bool 回答1: Not a full

问题 I've got a corrupt data frame with random header duplicates inside the data frame. How to ignore or delete these rows while loading the data frame? Since this random header is in the data frame, pandas raise an error while loading. I would like to ignore this row while loading it with pandas. Or delete it somehow, before loading it with pandas. The file looks like this: col1, col2, col3 0, 1, 1 0, 0, 0 1, 1, 1 col1, col2, col3 <- this is the random copy of the header inside the dataframe 0, 1

问题 I've got a corrupt data frame with random header duplicates inside the data frame. How to ignore or delete these rows while loading the data frame? Since this random header is in the data frame, pandas raise an error while loading. I would like to ignore this row while loading it with pandas. Or delete it somehow, before loading it with pandas. The file looks like this: col1, col2, col3 0, 1, 1 0, 0, 0 1, 1, 1 col1, col2, col3 <- this is the random copy of the header inside the dataframe 0, 1